Low-cost estimation and / or tracking of intrafocal displacement

Abstract

This invention provides a system / technique for facilitating low-cost estimation and / or tracking of intra-scan focal displacement. In various embodiments, the system enables a medical imaging scanner to perform an air scan. In various aspects, the system can access data generated by the medical imaging scanner and associated with the air scan, wherein this data may include a set of gantry angles swept by the X-ray tube during the air scan, wherein this data may include a set of intensity value matrices recorded by a multi-channel, multi-row detector during the air scan, and wherein each set of intensity value matrices corresponds to a set of gantry angles. In various cases, the system can calculate a set of cross-channel intensity slopes based on the set of intensity value matrices. In various cases, the system can apply a slope-displacement transfer function to the set of cross-channel intensity slopes to generate a set of focal displacements.

Description

Technical Field

[0001] This disclosure relates in general to the focal point of a medical imaging apparatus, and more specifically to the low-cost estimation and / or tracking of intra-scan focal point displacement. Background Technology

[0002] Inside the X-ray tube of a medical imaging apparatus, an electron beam is accelerated from the cathode to the anode to generate X-rays. The area where the electron beam strikes the anode is called the focal spot. Image artifacts can occur when the focal spot is in an unwanted and / or unintended location. Correcting or preventing such image artifacts may depend on tracking how the focal spot of the medical imaging apparatus moves during a medical imaging scan.

[0003] Systems and / or technologies that can solve one or more of these technical problems may be desirable. Summary of the Invention

[0004] The following summary is presented to provide a basic understanding of one or more embodiments of the invention. This summary is not intended to identify key or essential elements, nor is it intended to depict any scope of the specific embodiments or any scope of the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that follows. In one or more embodiments described herein, devices, systems, computer-implemented methods, apparatuses, and / or computer program products are described that facilitate low-cost estimation and / or tracking of intra-scan focal displacement.

[0005] According to one or more embodiments, a system is provided. The system may include a computer-readable storage device capable of storing computer-executable components. The system may also include a processor operatively coupled to the computer-readable storage device and capable of executing the computer-executable components stored in the computer-readable storage device. In various embodiments, the computer-executable components may include a scanning device that enables a medical imaging scanner to perform an air scan, wherein the medical imaging scanner may have an X-ray tube, a gantry, and / or a multi-channel, multi-row detector. In various aspects, the computer-executable components may also include a receiver device that accesses data generated by the medical imaging scanner and associated with the air scan, wherein the data may include a set of gantry angles scanned by the X-ray tube during the air scan, wherein the data may include a set of intensity value matrices recorded by the multi-channel, multi-row detector during the air scan, and / or wherein the set of intensity value matrices may each correspond to a set of gantry angles. In various cases, the computer-executable components may also include a slope device that can calculate a set of cross-channel intensity slopes based on the set of intensity value matrices, wherein the set of cross-channel intensity slopes may each correspond to a set of gantry angles. In various cases, the computer-executable component may also include a displacement component that applies a slope-displacement transfer function to a set of transchannel strength slopes, thereby generating a set of focal displacements that correspond to a set of rack angles. In various aspects, the computer-executable component may also include an actuation component that can initiate one or more electronic actions based on a set of focal displacements.

[0006] According to one or more implementation schemes, the above system can be implemented as a computer-implemented method and / or computer program product. Attached Figure Description

[0007] Figure 1 A block diagram of an exemplary, non-limiting system for facilitating low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein is shown.

[0008] Figure 2 An exemplary, non-limiting block diagram of a medical scanner according to one or more embodiments described herein is shown.

[0009] Figure 3 A block diagram of an exemplary, non-limiting system comprising air scan data is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein.

[0010] Figure 4 An exemplary, non-limiting block diagram illustrating air scan data including a set of rack angles and / or a set of intensity value matrices according to one or more embodiments described herein is shown.

[0011] Figure 5 An exemplary, non-limiting block diagram illustrating an intensity value matrix according to one or more embodiments described herein is shown.

[0012] Figure 6 A block diagram of an exemplary, non-limiting system comprising a set of row-averaged intensity value vectors is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein.

[0013] Figure 7 An exemplary, non-limiting block diagram illustrating a vector of row average intensity values ​​according to one or more embodiments described herein is shown.

[0014] Figure 8 An exemplary, non-limiting block diagram is shown illustrating how a row-average intensity value vector can be generated from an intensity value matrix according to one or more embodiments described herein.

[0015] Figure 9 A block diagram of an exemplary, non-limiting system comprising a set of cross-channel intensity slopes is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein.

[0016] Figure 10 An exemplary, non-limiting block diagram illustrating a set of cross-channel intensity slopes is shown according to one or more embodiments described herein.

[0017] Figure 11 An exemplary, non-limiting block diagram is shown illustrating how cross-channel intensity slopes can be generated from a vector of row average intensity values, according to one or more embodiments described herein.

[0018] Figure 12 A block diagram of an exemplary, non-limiting system comprising a slope-displacement transfer function and / or a set of focal displacements is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacements according to one or more embodiments described herein.

[0019] Figure 13 An exemplary, non-limiting block diagram illustrating how a set of focal displacements can be generated from a set of cross-channel intensity slopes, according to one or more embodiments described herein.

[0020] Figure 14 A block diagram of an exemplary, non-limiting system comprising a set of electronic actions is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein.

[0021] Figures 15 to 17Non-limiting, exemplary figures are shown according to one or more embodiments described herein.

[0022] Figures 18 to 20 A flowchart is shown of an exemplary, non-limiting computer implementation of a method for generating a slope-displacement transfer function according to one or more embodiments described herein.

[0023] Figure 21 A flowchart is shown of an exemplary, non-limiting computer-implemented method for facilitating low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein.

[0024] Figure 22 A block diagram is shown illustrating an exemplary, non-limiting operating environment in which one or more embodiments described herein may be facilitated.

[0025] Figure 23 An exemplary networking environment operable to perform the various specific implementations described herein is shown. Detailed Implementation

[0026] The following specific embodiments are merely exemplary and are not intended to limit the implementation and / or application or use of the embodiments. Furthermore, they are not intended to be construed as being bound by any express or implied information set forth in the foregoing "Background Art" or "Summary of the Invention" or "Detailed Description" sections.

[0027] One or more embodiments will now be described with reference to the accompanying drawings, wherein the same reference numerals are always used to denote the same elements. In the following description, numerous specific details are set forth for illustrative purposes in order to provide a more thorough understanding of one or more embodiments. However, it will be apparent that, in various cases, one or more embodiments may be practiced without these specific details.

[0028] Within the X-ray tube of a medical imaging device (e.g., a computed tomography (CT) scanner), an electron beam is accelerated from the cathode to the anode. When the electron beam strikes the anode, X-rays are generated. The surface area where the electron beam strikes may be referred to as the focal point (e.g., the focal point of the X-ray tube, and / or the focal point of the medical imaging device). Imaging artifacts (e.g., shadows, streaks, bands, rings) may occur when the position of the focal point changes undesirably and / or unintentionally. Correcting or preventing such imaging artifacts may depend on tracking how the focal point of the medical imaging device moves during a medical imaging scan.

[0029] For example, the X-ray tube of a medical imaging device may rotate around and / or along the gantry of the medical imaging device. Therefore, a medical imaging scan (e.g., a scanning protocol) may involve scanning the X-ray tube of the medical imaging device across a set of gantry angles (e.g., angular intervals around / along the gantry). At each gantry angle, the X-ray tube may emit one or more X-rays that may pass through an aperture in the gantry diametrically and / or radially, and such one or more X-rays may be captured / recorded by a detector (e.g., a multi-channel and / or multi-row detector) that rotates around / along the gantry to maintain an angle relative to the X-ray tube. Thus, at each gantry angle, the detector may be considered as a single "view" of any object (e.g., the anatomy of a medical patient) currently placed in the aperture of the gantry.

[0030] Unfortunately, as the X-ray tube rotates around / along the gantry, the focal spot of the X-ray tube may unintentionally change position (e.g., may shift and / or drift). This unintentional movement of the focal spot can be attributed to any number of reasons, such as the Earth's magnetic field interacting differently with the electron beam of the X-ray tube at different gantry angles, and / or to gravity interacting differently with the anode and / or cathode of the X-ray tube at different gantry angles. In any case, the position of the focal spot can undergo a change from gantry angle to gantry angle. Such a change in the focal spot position can be referred to as intra-scan focal spot displacement (e.g., since a single scan may involve sweeping the X-ray tube across multiple gantry angles). Such intra-scan focal spot displacement can cause significant imaging artifacts in medical imaging equipment, which may be undesirable.

[0031] To help correct, prevent, and / or otherwise reduce such imaging artifacts, estimating and / or tracking such intra-scan focal displacement may be beneficial. In other words, it may be helpful to know how and / or where the focal point moves during / throughout the scan before such imaging artifacts can be remedied. Those skilled in the art will understand that the instantaneous position of the X-ray tube's focal point can be determined experimentally using any suitable tungsten edge measurement technique. However, performing such a tungsten edge measurement technique for every possible gantry angle to which the X-ray tube can rotate would be extremely cumbersome, time-consuming, and / or resource-intensive. After all, the X-ray tube can typically rotate around / along the gantry at 360-degree intervals, and these 360-degree intervals can typically be broken down into hundreds or even thousands of gantry angles (e.g., hundreds and / or thousands of positions around / along the gantry to which the X-ray tube can rotate). Performing a tungsten edge measurement at each of these hundreds and / or thousands of gantry angles (e.g., at each of these hundreds and / or thousands of views) may be undesirable.

[0032] Furthermore, the intra-scan focal spot displacement can depend not only on the gantry angle but also on other configurable parameters of the medical imaging equipment (e.g., the anode-cathode voltage, anode-cathode current intensity, type of filter used, and focal spot size). There can be tens of thousands of different combinations and / or arrangements of possible gantry angles with possible parameter configurations of the medical imaging equipment. Performing tungsten edge measurements for each of these tens of thousands of combinations / arrangements would, of course, be quite cumbersome.

[0033] Therefore, systems and / or technologies that can solve one or more of these technical problems may be desirable.

[0034] The various embodiments described herein address one or more of these technical problems. These embodiments may include systems, computer-implemented methods, apparatus, and / or computer program products that facilitate low-cost estimation and / or tracking of intra-scan focal displacement. Specifically, the inventors of the various embodiments described herein have devised a technique capable of tracking, monitoring, and / or otherwise calculating intra-scan focal displacement of a medical imaging apparatus, without the cumbersome cost of applying tungsten edge measurements with every possible combination / permutation of gantry angles and configurable parameters. In particular, the inventors have devised novel metrics and / or features that can be calculated for medical imaging apparatuses, which can be used to facilitate low-cost estimation / tracking of intra-scan focal displacement. In various cases, this novel metric / feature may be a cross-channel intensity slope, as described herein.

[0035] More specifically, and as described above, when the X-ray tube of a medical imaging apparatus emits X-rays from a specific gantry angle (e.g., from a specific location surrounding / along the gantry of the medical imaging apparatus), such X-rays can be captured / recorded by the detectors of the medical imaging apparatus. Because the detectors can present a multi-channel and / or multi-row architecture, the output of the detector for that specific gantry angle can be a matrix of intensity values. In other words, the output can be a matrix of Hounsfield unit values, where each Hounsfield unit value corresponds to a specific row and a specific channel of the detector. In various aspects, the inventors recognize that the slope of such Hounsfield unit values ​​can be calculated and / or approximated across any suitable interval of the detector's channels. Furthermore, the inventors recognize that the value of this slope, which can be referred to as the cross-channel intensity slope, can be closely related to the location of the focal point of the X-ray tube of the medical imaging apparatus. That is, the inventors recognize that, given a known cross-channel intensity slope of the medical imaging apparatus, the location of the focal point of the medical imaging apparatus can be accurately predicted and / or inferred. Furthermore, calculating the transchannel intensity slope using every possible combination / permutation of the medical imaging equipment's gantry angle and configurable parameters significantly reduces time consumption, resource intensity, and / or hassle compared to performing tungsten edge measurements with each of these possible combinations / permutations. Therefore, the inventors have designed various systems and / or techniques described herein that can estimate and / or track intra-scan focal displacement in a low-cost and / or low-burden manner by utilizing transchannel intensity slope.

[0036] In various respects, the various embodiments described herein can be considered as computerized tools (e.g., any suitable combination of computer-executable hardware and / or computer-executable software) that facilitate low-cost estimation and / or tracking of intra-scan focal displacement. In various respects, such computerized tools may include scanning components, receiver components, averaging components, slope components, displacement components, and / or execution components.

[0037] In various embodiments, a medical scanner may be present, comprising an X-ray tube, a gantry, and / or a detector. In various aspects, the medical scanner may be any suitable type of medical imaging device (e.g., a CT scanner), as needed. In any case, the X-ray tube of the medical scanner may rotate about / along the gantry (e.g., in some cases, the X-ray tube may rotate 360 ​​degrees about the gantry; in others, the X-ray tube may rotate about the gantry at any other suitable angular interval). In various cases, the detector of the medical scanner may also rotate about / along the gantry such that the detector remains angularly opposite to the X-ray tube (e.g., such that the X-ray tube and the detector face each other across an opening in the gantry).

[0038] In various aspects, medical scanners may have a variety of controllable and / or configurable settings / parameters. In various cases, a controllable / configurable setting / parameter of a medical scanner may be a gantry angle (e.g., measured in degrees and / or radians). In other words, such a controllable / configurable setting / parameter can be considered as the angular position of the gantry rotated about / along the X-ray tube. As will be understood by those skilled in the art, a scan performed by a medical scanner (e.g., a scanning protocol) may involve scanning the X-ray tube across multiple gantry angles (e.g., scanning around / along the gantry at any suitable angular interval).

[0039] In various cases, another controllable / configurable setting / parameter of a medical scanner may be the anode-cathode voltage and / or anode-cathode current intensity. That is, such a controllable / configurable setting / parameter may be a voltage (e.g., measured in peak kilovolts) and / or current intensity (e.g., measured in milliamperes) applied to the X-ray tube to accelerate the electron beam from the cathode to the anode. As those skilled in the art will understand, a scan performed by a medical scanner (e.g., a scan protocol) may involve scanning the X-ray tube across multiple gantry angles while maintaining a constant anode-cathode voltage / current intensity. However, in other cases, a scan performed by a medical scanner (e.g., a scan protocol) may involve scanning the X-ray tube across multiple gantry angles with varying anode-cathode voltage / current intensities (e.g., such that different anode-cathode voltage / current intensities are applied to the X-ray tube at different gantry angles).

[0040] In various aspects, another controllable / configurable setting / parameter of a medical scanner can be the type of filter implemented in the X-ray tube. For example, in some cases, a planar filter can be used in the X-ray tube, and / or in others, a butterfly filter can be used.

[0041] In various cases, another controllable / configurable setting / parameter of a medical scanner can be the size of the focal spot of the X-ray tube. That is, this controllable / configurable setting / parameter can be the diameter and / or radius (e.g., measured in micrometers and / or millimeters) of the portion of the anode surface region struck and / or impacted by the electron beam. As those skilled in the art will understand, a scan performed by a medical scanner (e.g., a scan protocol) may involve scanning the X-ray tube across multiple gantry angles while keeping the X-ray tube at a constant focal spot size. However, in other cases, a scan performed by a medical scanner (e.g., a scan protocol) may involve scanning the X-ray tube across multiple gantry angles with varying focal spot sizes (e.g., such that different focal spot sizes are generated in the X-ray tube at different gantry angles).

[0042] In any case, it may be desirable to estimate and / or track the intra-scan focal displacement of a medical scanner. In other words, it may be desirable to determine how / where the focal spot of the X-ray tube moves as the X-ray tube rotates around the gantry. The computerized tools described herein can facilitate this estimation and / or tracking.

[0043] In various implementations, the scanning component of the computerized tool can electronically instruct and / or command the medical scanner to perform an air scan. That is, in the absence of an anatomical structure of an object and / or medical patient placed in the aperture of the gantry (e.g., only air is present in the aperture of the gantry), the scanning component can electronically cause the medical scanner to scan an X-ray tube across a set of gantry angles, wherein the X-ray tube can emit X-rays from each gantry angle, and wherein a detector can capture / record such X-rays for each gantry angle.

[0044] In various implementations, the receiver component of the computerized tool can electronically receive and / or otherwise electronically access air scan data generated during and / or in response to an air scan performed by a detector. In some cases, the receiver component can electronically retrieve air scan data from any suitable centralized and / or distributed data structure (e.g., graphical data structure, relational data structure, hybrid data structure), whether remote from the receiver component and / or local to the receiver component. In other cases, the receiver component can electronically retrieve air scan data from the medical scanner itself. In any case, the receiver component can electronically acquire and / or access the air scan data, enabling other components of the computerized tool to electronically interact with the air scan data (e.g., read, write, edit, manipulate).

[0045] In various aspects, air scan data can indicate / include a set of gantry angles swept by the X-ray tube during air scanning. In some cases, a set of gantry angles can be viewed as a set of "views" around / along the gantry. In various cases, air scan data can also indicate / include a set of intensity value matrices corresponding respectively (e.g., in a one-to-one manner) to a set of gantry angles. More specifically, for each particular gantry angle to which the X-ray tube rotates during air scanning, the detector can generate / produce a particular intensity value matrix (e.g., a matrix of Henry's unit values), where the particular intensity value matrix can be viewed as the result of the detector recording / capturing X-rays emitted by the X-ray tube from a particular gantry angle. As will be understood by those skilled in the art, the dimension of the intensity value matrix can depend on the physical architecture of the detector. For example, if the detector presents a multi-channel and multi-row structure with a channels and b rows, then for any suitable positive integers a and b, each intensity value matrix can be an a-by-b matrix of Henry's unit values ​​(e.g., or a b-by-a matrix), where each Henry's unit value can correspond respectively to a channel and a row of the detector.

[0046] In various implementations, the averaging component of a computerized tool can electronically calculate a set of row-averaged strength value vectors based on a set of row-averaged strength value matrices. In various aspects, a set of row-averaged strength value vectors may each correspond (e.g., in a one-to-one manner) to a set of strength value matrices and thus to a set of rack angles. For example, for any given strength value matrix, the averaging component can calculate / estimate the strength value vectors based on that given strength value matrix. Since that given strength value matrix may correspond to a particular rack angle, the calculated / estimated strength value vectors can be considered to also correspond to that particular rack angle. In any case, the averaging component can calculate / estimate the strength value vectors by averaging and / or taking the average of the rows of a given strength value matrix.

[0047] For example, as described above, when a medical scanner detector has *a* channels and *b* rows, the intensity value matrix generated by the detector can be an *a* x *b* matrix of Henlein unit values. For ease of explanation, assume that the elements (i, j) of the intensity value matrix can be the Henlein unit values ​​recorded by the *i*-th channel and the *j*-th row of the detector, where *i* is an integer between 1 and *a* including the end value, and *j* is an integer between 1 and *b* including the end value. In various aspects, the averaging component can calculate a first average intensity value (e.g., ...) of the Henlein unit values ​​recorded by the first channel across all rows. Where I(1,j) can be the Heinz unit value recorded by the first channel and the j-th row of the detector. Similarly, the averaging component can calculate the a-th average intensity value (e.g., the Heinz unit value recorded by the a-th channel across all rows). Where I(a,j) can be the Heinz unit values ​​recorded in the a-th channel and j-th row of the detector. Therefore, the first average intensity value to the a-th average intensity value can be considered as forming a vector with a total of a elements. This vector can be called the row average intensity value vector.

[0048] In any case, the average component can electronically calculate a set of row average intensity value vectors based on a set of intensity value matrices (e.g., one row average intensity value vector can be calculated for each intensity value matrix).

[0049] In various embodiments, the slope component of a computerized tool can electronically calculate a set of cross-channel intensity slopes based on a set of row-average intensity value vectors. In various aspects, a set of cross-channel intensity slopes can respectively correspond to (e.g., in a one-to-one manner) a set of row-average intensity value vectors and thus to a set of gantry angles. For example, for any given row-average intensity value vector, the slope component can calculate / estimate the cross-channel intensity slope based on the given row-average intensity value vector. Since the given row-average intensity value vector can correspond to a specific gantry angle, the calculated / estimated cross-channel intensity slope can be considered to also correspond to that specific gantry angle. In any case, the slope component can calculate / estimate the cross-channel intensity slope by fitting a trend line to the given row-average intensity value vector.

[0050] For example, as described above, when the detector of a medical scanner has a channels and b rows, the row-average intensity value vector can be an a-element vector of row-average Hounsfield unit values. For ease of explanation, assume that the element (i) of the row-average intensity value vector can be a scalar generated by averaging the Hounsfield unit values recorded across all b rows by the i-th channel of the detector, where i is an integer between 1 and a including the end values. In other words, the row-average intensity value vector can be considered to have one element per channel of the detector. In various aspects, the slope component can select any suitable interval of elements in the row-average intensity value vector and thus can select any suitable interval of channels. In some cases, the interval can be all a elements in the row-average intensity value vector (and thus all a channels) (e.g., the interval can extend from the first channel to the a-th channel). In other cases, the interval can be less than all a elements in the row-average intensity value vector (and thus less than all a channels) (e.g., the interval can extend from the q-th channel to the r-th channel, where q and r can be integers such that 1 ≤ q < r ≤ a). In any case, once the interval of elements is selected (e.g., once the channel interval is selected), the slope component can plot such an interval of elements in a graph and / or can fit a linear trend line to such a graph. In various aspects, the slope of such a linear trend line (which can have units and / or dimensions of Hounsfield units per channel) can be referred to as the cross-channel intensity slope.

[0051] In any case, the slope component can electronically calculate a set of cross-channel intensity slopes based on a set of row-average intensity value vectors (e.g., one cross-channel intensity slope can be calculated for each row-average intensity value vector).

[0052] In various implementations, the displacement component of the computerized tool can electronically calculate a set of focal displacements based on a set of transchannel strength slopes. In various aspects, a set of focal displacements may correspond individually (e.g., in a one-to-one manner) to a set of transchannel strength slopes and thus to a set of rack angles. For example, for any given transchannel strength slope, the displacement component can calculate / estimate the focal displacements based on that given transchannel strength slope (e.g., measured in micrometers and / or millimeters from a predetermined / desired focal location and / or along any suitable axis / direction). Since that given transchannel strength slope may correspond to a particular rack angle, the calculated / estimated focal displacements can also be considered to correspond to that particular rack angle.

[0053] In various cases, the displacement component can calculate / estimate focal displacement by applying a slope-displacement transfer function to a given transchannel intensity slope. In each case, the slope-displacement transfer function can be any suitable mathematical function and / or combination of mathematical functions that takes the transchannel intensity slope value (e.g., and / or the variation in the transchannel intensity slope value) as the independent variable and produces a focal displacement value (e.g., the variation in the position of the X-ray tube's focal spot measured along any suitable axis and / or direction) as the output. In various cases, the slope-displacement transfer function can be obtained experimentally, as explained in more detail herein.

[0054] In any case, because a set of focal displacements can correspond to a set of gantry angles, a set of focal displacements can be considered as describing how and / or where the focal spot of a medical scanner moves as the X-ray tube rotates around / along the gantry. In other words, a set of focal displacements can be considered as describing and / or representing the intra-scan focal spot movement of a medical scanner (e.g., it can be considered as a set of intra-scan focal displacements).

[0055] In various implementations, the execution components of a computerized tool can electronically initiate and / or perform one or more electronic actions based on a set of focal displacements. As a non-limiting example, in some aspects, the execution components can electronically plot a set of focal displacements against a set of rack angles on any suitable electronic display / monitor / screen. Thus, a medical professional can visually view this graph to see how the position of the medical scanner's focus changes with the rack angle. As another non-limiting example, in various cases, the execution components can electronically generate and / or electronically transmit maintenance recommendations based on a set of focal displacements. For example, the execution components can compare a set of focal displacements to any suitable threshold, and if a set of focal displacements fails to meet the threshold (e.g., if the largest focus in the set of focal displacements is above a maximum permissible displacement threshold), the execution components can recommend that the medical scanner should be maintained. In practice, in some cases, if a set of focal displacements fails to meet the threshold, the execution components can automatically schedule maintenance access to the medical scanner.

[0056] In any case, a set of focal displacements, each corresponding to a set of gantry angles, can be considered as representing and / or describing the intra-scan focal motion of a medical scanner.

[0057] To accurately identify a set of focal displacements, it may be necessary to first identify the slope-displacement transfer function. In various respects, the slope-displacement transfer function can depend on the medical scanner itself and can therefore be obtained experimentally and / or in a laboratory setting.

[0058] First, the baseline cross-channel slope of the medical scanner can be obtained. To obtain the baseline cross-channel slope, a partial air scan can be performed by the medical scanner. That is, with only air in the gantry aperture, the X-ray tube can emit X-rays from any single gantry angle, and the detector can record / capture such X-rays, thus producing a single intensity value matrix. Because this intensity value matrix can be the result of a partial air scan, it can be called an air-based intensity value matrix. In various cases, a row average (as described above) can be performed on the air-based intensity value matrix, thus producing a row-averaged intensity value vector. Because this row-averaged intensity value vector is based on a partial air scan, it can be called an air-based row-averaged intensity value vector. In various cases, the cross-channel slope (as described above) can be calculated by plotting a linear trend line and fitting it to any suitable interval of the air-based row-averaged intensity value vector. This cross-channel slope can be called the baseline cross-channel slope of the medical scanner.

[0059] Next, the baseline focal position of the medical scanner can be obtained. To obtain the baseline focal position, a partial edge scan can be performed by the medical scanner. That is, with only air in the gantry aperture and a tungsten edge placed between the anode and cathode, the X-ray tube can emit X-rays from the same gantry angle used for the baseline cross-channel slope, and the detector can capture / record such X-rays, thereby producing a single intensity value matrix. Because this intensity value matrix can be the result of a partial edge scan, it can be called an edge-based intensity value matrix. In various respects, normalization can be facilitated by dividing the edge-based intensity value matrix by the air-based intensity value matrix element-wise, thereby producing a normalized edge-based intensity value matrix. As those skilled in the art will understand, a point spread function can be derived from the normalized edge-based intensity value matrix (e.g., a line spread function can be derived first, and then a point spread function can be derived from the line spread function). Because the point spread function can be considered as a multidimensional Gaussian distribution, the centroid of the point spread function can be considered as representing the focal point of the medical scanner. Therefore, the location of the centroid of the point spread function can be considered as the baseline focal position of the medical scanner.

[0060] Now, for any suitable number of iterations, the focus of the medical scanner can be perturbed by injecting a known positional offset, and both the perturbed cross-channel slope and the perturbed focus position can be obtained as described above (e.g., in the same manner as obtaining the baseline cross-channel slope and baseline focus position). For example, after injecting the known positional offset, the perturbed cross-channel slope can be obtained by performing a partial air scan at the same gantry angle as described above, thereby generating a perturbed air-based intensity value matrix; performing a row average on the perturbed air-based intensity value matrix, thereby generating a perturbed air-based row-averaged intensity value vector; and plotting a linear trend line and fitting it to the perturbed air-based row-averaged intensity value vector, thereby generating the perturbed cross-channel slope. Furthermore, after injecting a known positional offset, the focal position of the disturbance can be obtained by performing a partial edge scan at the same rack angle as described above, thereby generating an edge-based intensity value matrix; normalizing the edge-based intensity value matrix of the disturbance by dividing it by the air-based intensity value matrix of the disturbance, thereby generating a normalized edge-based intensity value matrix of the disturbance; and deriving the point spread function of the disturbance from the normalized edge-based intensity value matrix of the disturbance, wherein the position of the centroid of the point spread function of the disturbance can be regarded as the focal position of the disturbance.

[0061] In each respect, such perturbations (e.g., such injection of a known position offset) can be performed any suitable number of iterations (e.g., injecting a different and / or unique position offset at each iteration) to produce a set of perturbations with cross-channel slopes and a set of perturbation focal positions that can correspond to each other.

[0062] Next, the change in a set of cross-channel slopes can be calculated by subtracting the baseline cross-channel slope from the cross-channel slope of each perturbation in the set of perturbation slopes. Similarly, the focal displacement of a set of perturbations can be calculated by subtracting the baseline focal position from the focal position of each perturbation in the set of perturbation focal positions. It should be noted that the focal displacement of a set of perturbations can be considered as corresponding to (e.g., in a one-to-one manner) the changes in a set of cross-channel slopes.

[0063] In various cases, a set of perturbation focal displacements can be plotted for changes in a set of cross-channel slopes, and any suitable trend line (e.g., linear, quadratic, exponential, logarithmic, polynomial) can be fitted to this graph. In all respects, this trend line can be considered a slope-displacement transfer function because it takes the change in cross-channel slope as the independent variable and produces focal displacements as the output. Therefore, in this way, the slope-displacement transfer function can be obtained experimentally.

[0064] As those skilled in the art will understand, the slope-displacement transfer function can depend on the controllable / configurable parameters / settings of the medical scanner. For example, when the medical scanner is configured to utilize a specific anode-cathode voltage / current intensity, a specific filter, and / or a specific focal size, the above experimental procedure can be performed to produce a specific slope-displacement transfer function. In various cases, when the medical scanner is configured to utilize different anode-cathode voltage / current intensities, different filters, and / or different focal sizes, the above experimental procedure can be repeated to produce different slope-displacement transfer functions. In this way, different transfer functions can be obtained for different configurations of the medical scanner.

[0065] It should be noted that, in various respects, the number of tungsten edge measurements performed to obtain the slope-displacement transfer function (e.g., the number of partial edge scans) can be significantly less than the number of tungsten edge measurements required if instead one tungsten edge measurement were performed for each possible gantry angle of the medical scanner. In fact, as mentioned above, there can typically be hundreds or even thousands of gantry angles around / along the gantry of a medical scanner. Therefore, tracking the intra-scan focal displacement solely via tungsten edge measurements would require performing hundreds or even thousands of such tungsten edge measurements (e.g., one partial edge scan for each gantry angle). This would be extremely time-consuming and cumbersome. Furthermore, such costs / burdens would be exacerbated by the increased variability of other configurable / controllable parameters / settings of the medical scanner (e.g., a unique tungsten edge measurement would be required for each unique combination of gantry angle, anode-cathode voltage / current intensity, filter type, and / or focal size).

[0066] In stark contrast, the slope-displacement transfer function described herein can be obtained using far fewer tungsten edge measurements. In fact, for any given anode-cathode voltage / current intensity, for any given filter, and / or for any given focal size, an accurate slope-displacement transfer function can be obtained using as few as tens and / or hundreds of tungsten edge measurements (e.g., tens and / or hundreds of partial edge scans, tens and / or hundreds of perturbations). In other words, estimating and / or tracking the intra-scan focal displacement via the slope-displacement transfer function, as described herein, is likely far less costly in terms of time, workload, and / or other resources compared to estimating / tracking the intra-scan focal displacement solely via tungsten edge measurements.

[0067] Therefore, the various implementations described herein can be considered as computerized tools that can electronically estimate / track intra-scan focal displacement of a medical scanner in a low-cost manner by utilizing cross-channel intensity slope and / or slope-displacement transfer functions.

[0068] The various implementations described herein can be used to solve inherently highly technical problems (e.g., to facilitate low-cost estimation and / or tracking of intra-scan focal displacement) using hardware and / or software, problems that are not abstract and cannot be performed as a set of human mental behaviors. Furthermore, some processes performed can be executed by a dedicated computer (e.g., X-ray tube, gantry, multi-channel multi-row detector) to perform defined tasks related to the low-cost estimation / tracking of intra-scan focal displacement. For example, such defined tasks may include: a device operatively coupled to a processor causing a medical imaging scanner to perform an air scan, wherein the medical imaging scanner has an X-ray tube, a gantry, and a multi-channel, multi-row detector; the device accessing data generated by the medical imaging scanner and associated with the air scan, wherein the data includes a set of gantry angles swept by the X-ray tube during the air scan, wherein the data includes a set of intensity value matrices recorded by the multi-channel, multi-row detector during the air scan, and wherein each set of intensity value matrices corresponds to a set of gantry angles; the device calculating a set of cross-channel intensity slopes based on the set of intensity value matrices, wherein each set of cross-channel intensity slopes corresponds to a set of gantry angles; the device applying a slope-displacement transfer function to the set of cross-channel intensity slopes to generate a set of focal displacements corresponding to the set of gantry angles; and / or the device initiating one or more electronic actions based on the set of focal displacements. In various cases, such one or more electronic actions may include the device plotting a set of focal displacements for a set of gantry angles on an electronic display.

[0069] Such defined tasks are not performed manually by humans. In fact, neither the human brain nor a person carrying pen and paper can: electronically cause a medical scanner (e.g., a CT scanner) to perform an air scan; electronically access the Heinz matrix recorded by the multi-channel, multi-row detectors of such a medical scanner; electronically calculate slope values ​​based on such a Heinz matrix; and / or electronically apply a slope-displacement transfer function to such slope values ​​to produce a set of intra-scan focal displacements. Instead, the various embodiments described herein are inherently and inextricably linked to computer technology and cannot be implemented outside of a computing environment (e.g., a medical imaging scanner is an inherently computerized device capable of generating medical images by passing X-ray radiation through an object of interest (such as the anatomy of a patient); a computerized tool capable of estimating and / or tracking the position of the focal point of such a medical imaging scanner based on air scan data generated by the scanner without having to perform tungsten edge measurements at every possible gantry angle is also inherently computerized and cannot be implemented in any sensible, practical, or reasonable manner without a computer).

[0070] Furthermore, various implementations can incorporate the teachings described herein regarding the low-cost estimation and / or tracking of intra-scan focal displacement into practical applications. As mentioned above, one possible way to measure / track intra-scan focal displacement would be to perform tungsten edge measurements (e.g., partial edge scanning) at each possible gantry angle of the medical imaging scanner. However, this would be very cumbersome and time-consuming. To address this problem, the inventors have devised various techniques for estimating / tracking intra-scan focal displacement using cross-channel slopes. More specifically, the medical imaging scanner can perform an air scan, which may involve scanning the X-ray tube of the medical imaging scanner across a set of gantry angles and recording an intensity value matrix at each gantry angle using the multi-channel, multi-row detectors of the medical imaging scanner. Row averaging can then be performed on each intensity value matrix to produce a set of row-averaged intensity value vectors. Next, a set of cross-channel slopes can be generated by fitting a linear trend line to each row-averaged intensity value vector in the row-averaged intensity value vectors. Finally, a slope-displacement transfer function can be applied to the set of cross-channel slopes to produce a set of focal displacements corresponding to the set of gantry angles respectively. In various cases, a set of focal displacements can be considered as representing how and / or where the focus of a medical imaging scanner moves as the X-ray tube rotates around / along the gantry. That is, a set of focal displacements can be considered as indicating / representing the intra-scan movement of the focus. While this technique does involve calculating the cross-channel slope for each gantry angle, such calculations can be far less burdensome and / or time-consuming compared to performing tungsten edge scans for each gantry angle. Furthermore, although the slope-displacement transfer function can be obtained experimentally using tungsten edge measurements, the number of tungsten edge measurements required to accurately identify the slope-displacement transfer function is orders of magnitude smaller than that required to perform individual tungsten edge measurements for each gantry angle. Therefore, in any case, the various embodiments described herein allow for the estimation and / or tracking of intra-scan focal displacements in a significantly less costly manner compared to the possible approach if individual tungsten edge measurements were performed for each gantry angle. Computerized tools capable of estimating / tracking intra-scan focal displacements in this low-cost manner undoubtedly constitute a concrete and tangible technical improvement in the field of focus for medical imaging scanners and are therefore certainly qualified as a useful and practical application of computers.

[0071] Furthermore, it must be emphasized that the various embodiments described herein do not merely involve a lack of significantly more mathematical calculations. In fact, as described herein, the inventors have devised an efficient and low-cost technique for estimating / tracking the motion of the intra-scan focus. Unlike performing tungsten edge measurements at every possible rack angle, this efficient and low-cost technique involves calculating the cross-channel intensity slope at each rack angle and applying a slope-displacement transfer function to such cross-channel intensity slopes. Note that the specific details used to implement / describe this functionality are presented herein as a series of steps, actions, and / or mathematical estimations / calculations performed by a computer processor, as there is simply no other way to intelligently discuss the subject matter innovation. Although the subject matter innovation utilizes and / or involves such mathematical estimations / calculations, it remains a practical technical solution to a real-world technical problem. After all, and as illustrated herein, estimating / tracking the motion of the intra-scan focus via the calculation of cross-channel slopes is such a novel technique that it is far less burdensome in terms of time, workload, and resources compared to performing individual tungsten edge measurements at each rack angle. The fact that the subject matter innovation involves mathematical concepts does not negate or refute this technical benefit.

[0072] Furthermore, the various embodiments described herein can control real-world physical devices based on the disclosed teachings. For example, the various embodiments described herein can electronically control (e.g., power on, power off, calibration, engagement, disengagement) a real-world medical imaging scanner (e.g., a CT scanner) having a real-world X-ray tube, a real-world gantry, and / or a real-world multi-channel, multi-row detector.

[0073] It should be understood that the accompanying figures and descriptions provided herein are non-limiting examples and are not necessarily drawn to scale.

[0074] Figure 1 A block diagram of an exemplary, non-limiting system 100 that facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein is shown. As shown, the intra-scan focal tracking system 102 can be electronically integrated with a medical scanner 104 via any suitable wired and / or wireless electronic connection.

[0075] In various embodiments, the medical scanner 104 may be any suitable medical imaging device as needed. For example, in various aspects, the medical scanner 104 may be a CT scanner. In any case, the medical scanner 104 may include an X-ray tube 106, a gantry 108, and / or a detector 110. In various aspects, the X-ray tube 106 may be rotated to different angular positions around and / or along the gantry 108. In various aspects, the detector 110 may also be rotated around / along the gantry 108 to maintain an angle relative to the X-ray tube 106 (e.g., the angular position of the detector 110 may differ from the angular position of the X-ray tube 106 by 180 degrees). Furthermore, in various aspects, the X-ray tube 106 may include a cathode (not shown) and an anode (not shown), wherein a voltage applied to such a cathode and anode can accelerate an electron beam from the cathode to the anode. When the electron beam strikes the anode, X-ray radiation may be generated, and this X-ray radiation may radiate and / or propagate toward the central aperture of the gantry 108. When an object (e.g., the anatomy of a medical patient) is placed within the central aperture of gantry 108, X-ray radiation can pass through the object and be recorded by detector 110, thereby producing a medical image (e.g., a CT image). Relative to Figure 2 This is illustrated.

[0076] Figure 2 An exemplary, non-limiting block diagram 200 of a medical scanner according to one or more embodiments described herein is shown. In other words, Figure 2 A non-limiting exemplary embodiment of a medical scanner 104 is shown. As shown, the gantry 108 may be a circular path and / or ring, around which both the X-ray tube 106 and the detector 110 may be controllably rotated. As a non-limiting example, the X-ray tube 106 may radially emit one or more X-rays 202 toward a central aperture of the gantry 108, and the emission direction of the X-rays 202 may be altered by moving the X-ray tube 106 around / along the gantry 108 in a rotational direction 204. Furthermore, the detector 110 may also rotate in the rotational direction 204 to maintain an angular relationship with the X-ray tube 106, thereby allowing the detector 110 to capture and / or record the X-rays 202.

[0077] Although not in Figure 2 As explicitly shown, but will be understood by those skilled in the art, detector 110 may present any suitable architecture as required. For example, in some cases, detector 110 may present a multi-channel and / or multi-row architecture. In this case, detector 110 may have a circumferential orientation along rack 108 (e.g., in...). Figure 2 The detector 110 may have any suitable number of detector channels positioned in the xy plane, and the detector 110 may have any suitable number of detector channels positioned along the longitudinal / hole direction of the frame 108 (e.g., along the xy plane). Figure 2any appropriate number of detector rows (located along the z-axis).

[0078] As will be further understood by those skilled in the art, the positioning and / or location of the X-ray tube 106 along the gantry 108 can be described by gantry angles (e.g., measured in degrees and / or radians), wherein the sign of the gantry angle indicates the direction in which the X-ray tube 106 has rotated about / along the gantry 108 from a reference position (e.g., counterclockwise and / or clockwise), and / or wherein the magnitude of the gantry angle indicates how far the X-ray tube 106 has rotated about / along the gantry 108 from a reference position.

[0079] In any case, as the X-ray tube 106 rotates around / along the gantry 108, the focal spot of the medical scanner 104 may shift, drift, and / or otherwise move. As described above, this movement, which may be referred to as intra-scan focal spot displacement, can be caused by gravity and / or the Earth's magnetic field, which interact differently with the X-ray tube 106 at different gantry angles. Unfortunately, this intra-scan focal spot displacement can cause the detector 110 to record significant imaging artifacts (e.g., noticeable image streaks, noticeable image shadows, bands, rings). Correction and / or reduction of such imaging artifacts may depend on estimating, tracking, and / or otherwise measuring how the position of the focal spot changes as the X-ray tube 106 rotates around / along the gantry 108. As described herein, the intra-scan focal spot tracking system 102 can facilitate such estimation, tracking, and / or measurement in a low-cost and / or low-incurance manner.

[0080] Re-reference Figure 1 In various embodiments, the intra-scan focus tracking system 102 may include a processor 112 (e.g., a computer processing unit, microprocessor) and a computer-readable memory 114 operatively and / or communicatively connected to / coupled to the processor 112. The computer-readable memory 114 may store computer-executable instructions that, when executed by the processor 112, cause the processor 112 and / or other components of the intra-scan focus tracking system 102 (e.g., scanning component 116, receiver component 118, averaging component 120, slope component 122, displacement component 124, and / or execution component 126) to perform one or more actions. In various embodiments, the computer-readable memory 114 may store computer-executable components (e.g., scanning component 116, receiver component 118, averaging component 120, slope component 122, displacement component 124, and / or execution component 126), and the processor 112 may execute the computer-executable components.

[0081] In various embodiments, the intrafocal tracking system 102 may include a scanning component 116. In various aspects, as described herein, the scanning component 116 may electronically instruct, command, and / or otherwise cause the medical scanner 104 to perform an air scan.

[0082] In various embodiments, the intrafocal tracking system 102 may also include a receiver component 118. In various cases, as described herein, the receiver component 118 may electronically receive, retrieve, and / or access data generated during and / or in response to an air scan performed by the medical scanner 104. In various cases, this data may include a set of gantry angles scanned by the X-ray tube 106 during the air scan, and / or the data may also include a matrix of intensity values ​​recorded by the detector 110 and corresponding to a set of gantry angles.

[0083] In various embodiments, the scanning in-focus tracking system 102 may also include an averaging component 120. In various aspects, as described herein, the averaging component 120 may electronically perform row averaging on a set of intensity value matrices to produce a set of row-averaged intensity value vectors.

[0084] In various embodiments, the scanning in-focus tracking system 102 may also include a slope component 122. In various cases, as described herein, the slope component 122 may electronically calculate a set of cross-channel intensity slopes based on a set of row-averaged intensity value vectors.

[0085] In various embodiments, the scanning in-focus tracking system 102 may also include a displacement component 124. In various aspects, as described herein, the displacement component 124 may electronically calculate a set of focus displacements based on a set of transchannel intensity slopes via a slope-displacement transfer function.

[0086] In various embodiments, the in-scan focus tracking system 102 may also include an execution element 126. In various cases, as described herein, the execution element 126 may electronically perform one or more electronic actions based on a set of focus displacements (e.g., drawing a set of focus displacements for a set of rack angles, making electronic recommendations by comparing a set of focus displacements with a threshold).

[0087] Figure 3 A block diagram of an exemplary, non-limiting system 300 comprising air scan data, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein, is shown. As shown, in some cases, system 300 may include the same components as system 100 and may also include air scan data 302.

[0088] In various embodiments, scanning element 116 may electronically instruct, electronically command, and / or otherwise electronically cause medical scanner 104 to perform an air scan. That is, with only air in the aperture of gantry 108, X-ray tube 106 may scan through any suitable set of gantry angles. At each gantry angle, X-ray tube 106 may radially emit X-rays through the aperture of gantry 108, and detector 110 may capture / record such X-rays. In various cases, electronic data generated by medical scanner 104 during, in response to, and / or otherwise due to such air scan can be considered as air scan data 302.

[0089] In various embodiments, receiver component 118 may electronically receive and / or otherwise electronically access air scan data 302. In various cases, receiver component 118 may electronically retrieve air scan data 302 from any suitable centralized and / or distributed data structure (not shown). In various other cases, receiver component 118 may electronically retrieve air scan data 302 from the medical scanner 104 itself. In any case, receiver component 118 may electronically acquire and / or access air scan data 302, enabling other components of the intra-scan focus tracking system 102 to electronically interact with the air scan data 302.

[0090] In all respects, the air scan data 302 can be any suitable electronic data structure, which includes / represents a set of gantry angles scanned by the X-ray tube 106 during the air scan and / or includes / represents a matrix of intensity values ​​recorded by the detector 110 during the air scan. This will be relative to Figures 4 to 5 Further explanation.

[0091] Figure 4 An exemplary, non-limiting block diagram 400 is shown, illustrating air scan data including a set of rack angles and / or a matrix of intensity values, according to one or more embodiments described herein. That is, Figure 4 A non-limiting, exemplary embodiment of air scan data 302 is depicted. As shown, air scan data 302 may indicate and / or include a set of rack angles 402 and / or a matrix 404 of intensity values ​​corresponding to a set of rack angles 402 respectively.

[0092] In various respects, a set of gantry angles 402 may be a set of gantry angles (e.g., angle intervals) that the X-ray tube 106 scans around / along the gantry 108 during an air scan. In various cases, a set of gantry angles 402 may include n angle values ​​(e.g., measured in degrees and / or radians) supporting any suitable positive integer n: gantry angle 1 to gantry angle n. For example, gantry angle 1 may be considered as a scalar representing a first position rotated around / along the gantry 108 and to by the X-ray tube 106 during an air scan, and gantry angle n may be considered as a scalar representing an nth position rotated around / along the gantry 108 and to by the X-ray tube 106 during an air scan.

[0093] In various aspects, a set of intensity value matrices 404 may represent the electronic output of detector 110 during and / or in response to an air scan. In various cases, the set of intensity value matrices 404 may correspond to a set of gantry angles 402 respectively (e.g., in a one-to-one manner). Therefore, in various cases, the set of intensity value matrices 404 may include n matrices: intensity value matrix 1 to intensity value matrix n. More specifically, intensity value matrix 1 can be considered as the output of detector 110 when X-ray tube 106 emits X-rays at gantry angle 1 during an air scan. Similarly, intensity value matrix n can be considered as the output of detector 110 when X-ray tube 106 emits X-rays at gantry angle n during an air scan. As will be understood by those skilled in the art, the dimension and / or format of each intensity value matrix may depend on the architecture of detector 110. Relative to Figure 5 This is described further.

[0094] Figure 5 An exemplary, non-limiting block diagram 500 illustrating an intensity value matrix according to one or more embodiments described herein is shown. That is, Figure 5 An exemplary, non-limiting embodiment of any one of the intensity value matrices 404 is depicted.

[0095] In various implementations, an intensity value matrix 502 may exist. In various aspects, intensity value matrix 502 can be any one of a set of intensity value matrices 404. In various cases, detector 110 may have s detector channels supporting any suitable positive integer s: detector channel 1 to detector channel s. In various cases, detector channels 1 to detector channel s can be considered to collectively form a set of detector channels 504. In various aspects, detector 110 may have t detector rows supporting any suitable positive integer t: detector row 1 to detector row t. In various cases, detector row 1 to detector row t can be considered to collectively form a set of detector rows 506. Because detector 110 may have s channels and t rows, intensity value matrix 502 may be, as shown, an s x t matrix, where each element of such an s x t matrix corresponds to a specific channel and a specific row of detector 110, respectively. For example, the intensity value 1(1) of the intensity value matrix 502 can be a scalar Henle unit value measured, captured, and / or otherwise recorded by detector channel 1 and detector row 1 of detector 110 when X-ray tube 106 is positioned at a specific gantry angle in a set of gantry angles 402. Similarly, the intensity value 1(t) of the intensity value matrix 502 can be a scalar Henle unit value measured, captured, and / or otherwise recorded by detector channel 1 and detector row t of detector 110 when X-ray tube 106 is positioned at that specific gantry angle. Furthermore, the intensity value s(1) of the intensity value matrix 502 can be a scalar Henle unit value measured, captured, and / or otherwise recorded by detector channel s and detector row 1 of detector 110 when X-ray tube 106 is positioned at that specific gantry angle. For example, the intensity values ​​s(t) of the intensity value matrix 502 can be scalar Heinz unit values ​​measured, captured, and / or otherwise recorded by the detector channels s and detector rows t of the detector 110 when the X-ray tube 106 is positioned at that particular gantry angle.

[0096] Figure 6 A block diagram 600 of an exemplary, non-limiting system comprising a set of line average intensity value vectors is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein. As shown, in some cases, system 600 may include the same components as system 300 and may also include a set of line average intensity value vectors 602.

[0097] In various implementations, the averaging component 120 may electronically generate, electronically calculate, and / or otherwise electronically estimate a set of row average intensity value vectors 602 based on air scan data 302. Relative to Figures 7 to 8 This was explained in more detail.

[0098] Figure 7An exemplary, non-limiting block diagram 700 illustrating a vector of row average intensity values ​​according to one or more embodiments described herein is shown. That is, Figure 7 A non-limiting, exemplary implementation of a set of row average intensity value vectors 602 is described.

[0099] As shown in the figure, a set of row average intensity value vectors 602 can correspond to a set of intensity value matrices 404 (e.g., in a one-to-one manner). Therefore, since a set of intensity value matrices 404 can include n matrices, a set of row average intensity value vectors 602 can include n vectors: row average intensity value vector 1 to row average intensity value vector n. In other words, each intensity value matrix can have one row average intensity value vector. For example, row average intensity value vector 1 can correspond to intensity value matrix 1. That is, the averaging component 120 can electronically calculate row average intensity value vector 1 based on (e.g., through mathematical manipulation) intensity value matrix 1. Furthermore, since row average intensity value vector 1 can correspond to intensity value matrix 1, and since intensity value matrix 1 can correspond to rack angle 1, row average intensity value vector 1 can be considered to correspond to rack angle 1. Similarly, row average intensity value vector n can correspond to intensity value matrix n. Again, this can mean that the averaging component 120 can electronically calculate row average intensity value vector n based on (e.g., through mathematical manipulation) intensity value matrix n. Furthermore, since the row average strength value vector n can correspond to the strength value matrix n, and since the strength value matrix n can correspond to the rack angle n, the row average strength value vector n can be considered to correspond to the rack angle n. In various cases, each row average strength value vector in a set of row average strength value vectors 602 can be calculated by performing a row average on the corresponding strength value matrix in a set of strength value matrices 404. Relative to Figure 8 This was explained in more detail.

[0100] Figure 8 An exemplary, non-limiting block diagram 800 is shown illustrating how a row average intensity value vector can be generated from an intensity value matrix according to one or more embodiments described herein.

[0101] In various aspects, the intensity value matrix 502 can be as described above. In various cases, the averaging component 120 can electronically generate a row average intensity value vector 802 based on the intensity value matrix 502. In other words, the intensity value matrix 502 can be any one of a set of intensity value matrices 404, and the row average intensity value vector 802 can be an average intensity value vector corresponding to the intensity value matrix 502 in a set of row average intensity value vectors 602. In various cases, the averaging component 120 can generate the row average intensity value vector 802 by performing row averaging on the intensity value matrix 502. More specifically, since the detector 110 can have s channels and t rows, the intensity value matrix 502 can be an s-by-t matrix of Henlein unit values, as described above, and the row average intensity value vector 802 can be an s-element vector of average Henlein unit values. That is, the row average intensity value vector 802 can have s elements: row average intensity value 1 to row average intensity value s. In various respects, the row average intensity value 1 can be the average (e.g., mean) of all Hennessy unit values ​​associated with detector channel 1 in intensity value matrix 502. In other words, the row average intensity value 1 can be equal to (and / or otherwise based on) the average (e.g., mean) of intensity values ​​1(1) to 1(t). Similarly, in various cases, the row average intensity value s can be the average (e.g., mean) of all Hennessy unit values ​​associated with detector channel s in intensity value matrix 502. In other words, the row average intensity value s can be equal to (and / or otherwise based on) the average (e.g., mean) of intensity values ​​s(1) to s(t). Therefore, in various cases, the row average intensity value vector 802 can be considered as the result of averaging a set of detector rows 506 from intensity value matrix 502.

[0102] In any case, the average component 120 can generate a set of row average intensity value vectors 602 based on the air scan data 302.

[0103] Figure 9 A block diagram of an exemplary, non-limiting system 900 comprising a set of transchannel intensity slopes is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein. As shown, in some cases, system 900 may include the same components as system 600 and may also include a set of transchannel intensity slopes 902.

[0104] In various implementations, the slope component 122 may electronically generate, electronically calculate, and / or otherwise electronically estimate a set of transchannel intensity slopes 902 based on a set of row-averaged intensity value vectors 602. Relative to Figures 10 to 11 This was explained in more detail.

[0105] Figure 10An exemplary, non-limiting block diagram illustrating a set of cross-channel intensity slopes is shown according to one or more embodiments described herein. That is, Figure 10 A set of non-limiting, exemplary embodiments with a cross-channel strength slope of 902 are described.

[0106] As shown in the figure, a set of cross-channel strength slopes 902 can correspond to a set of row average strength value vectors 602 (e.g., in a one-to-one manner). Therefore, since a set of row average strength value vectors 602 can include n vectors, a set of cross-channel strength slopes 902 can include n slopes: cross-channel strength slope 1 to cross-channel strength slope n. In other words, each row average strength value vector can have one cross-channel strength slope. For example, cross-channel strength slope 1 can correspond to row average strength value vector 1. That is, the slope component 122 can electronically calculate the cross-channel strength slope 1 based on (e.g., through mathematical manipulation) row average strength value vector 1. Furthermore, since cross-channel strength slope 1 can correspond to row average strength value vector 1, and since row average strength value vector 1 can correspond to rack angle 1, cross-channel strength slope 1 can be considered to correspond to rack angle 1. Similarly, cross-channel strength slope n can correspond to row average strength value vector n. Furthermore, this means that the slope component 122 can electronically calculate the cross-channel strength slope n based on (e.g., through mathematical manipulation) the row average strength value vector n. Additionally, since the cross-channel strength slope n can correspond to the row average strength value vector n, and since the row average strength value vector n can correspond to the rack angle n, the cross-channel strength slope n can be considered to correspond to the rack angle n. In various cases, each cross-channel strength slope in a set of cross-channel strength slopes 902 can be calculated by fitting a linear trend line to a corresponding row average strength value vector in a set of row average strength value vectors 602. Relative to Figure 11 This was explained in more detail.

[0107] Figure 11 An exemplary, non-limiting block diagram 1100 is shown illustrating how cross-channel intensity slopes can be generated from a vector of row average intensity values, according to one or more embodiments described herein.

[0108] In various aspects, the row average intensity value vector 802 can be as described above. In various cases, the slope component 122 can electronically generate the cross-channel intensity slope 1102 based on the row average intensity value vector 802. In other words, the row average intensity value vector 802 can be any one of the set of row average intensity value vectors 602, and the cross-channel intensity slope 1102 can be one of the set of cross-channel intensity slopes 902 corresponding to the row average intensity value vector 802. In various cases, the cross-channel intensity slope 1102 can be a scalar equal to (and / or otherwise based on) the slope of a linear trend line fitted to the row average intensity value vector 802.

[0109] Specifically, in various aspects, the slope component 122 can select any suitable consecutive interval of channels from a set of detector channels 504. In some cases, the slope component 122 can select the entire set of detector channels 504 as the consecutive interval (e.g., the interval from detector channel 1 to detector channel s can be selected). In other cases, the slope component 122 can select less than the entire set of detector channels 504 as the consecutive interval (e.g., the interval from detector channel u to detector channel v can be selected, supporting any suitable integers u and v, where 1 ≤ u < v ≤ s). In any case, since the row average intensity value vector 802 can have one element (e.g., one intensity value) per detector channel, selecting a consecutive interval of channels from the set of detector channels 504 can be considered analogous to and / or equivalent to selecting a corresponding consecutive interval of elements from the row average intensity value vector 802. For example, selecting a consecutive interval of channels starting from detector channel u and ending at detector channel v can be considered corresponding to a consecutive interval of elements of the row average intensity value vector 802 starting from row average intensity value u and ending at row average intensity value v. In various aspects, the slope component 122 can plot such a consecutive interval of elements of the row average intensity value vector 802. In various cases, the slope component 122 can fit a linear trend line and / or the best fit line to such a graph via any suitable technique (e.g., the least squares method). In various cases, the slope of such a linear trend line and / or best fit line can be considered to be the cross-channel intensity slope 1102.

[0110] Although a consecutive interval of channels and / or elements of the row average intensity value vector 802 is described herein, this is merely a non-limiting example for ease of explanation. Those of ordinary skill in the art will understand that in various cases, a non-consecutive interval of channels and / or elements of the row average intensity value vector 802 can be plotted and / or fitted to generate the cross-channel intensity slope 1102.

[0111] In any case, the slope component 122 can generate a set of cross-channel intensity slopes 902 based on a set of row average intensity value vectors 602.

[0112] Figure 12 A block diagram of an exemplary, non-limiting system 1200, comprising a slope-displacement transfer function and / or a set of focus displacements, is shown, according to one or more embodiments described herein, which facilitates low-cost estimation and / or tracking of intra-scan focus displacements. As shown, in some cases, system 1200 may include the same components as system 900 and may also include a slope-displacement transfer function 1202 and / or a set of focus displacements 1204.

[0113] In various embodiments, the displacement component 124 may electronically store, maintain, control, and / or otherwise electronically access the slope-displacement transfer function 1202. In various aspects, the slope-displacement transfer function 1202 may be any suitable mathematical function and / or combination of mathematical functions that can take the cross-channel intensity slope (and / or the variation of the cross-channel intensity slope) as input variables and produce a focal displacement as output. Additional details regarding how the slope-displacement transfer function 1202 can be identified and / or obtained will be referred to... Figures 18 to 20 Let's have a discussion.

[0114] In any case, the displacement component 124 can electronically generate a set of focal displacements 1204 by applying a slope-displacement transfer function 1202 to a set of transchannel intensity slopes 902. Relative to Figure 13 This point was discussed in more detail.

[0115] Figure 13 An exemplary, non-limiting block diagram 1300 is shown illustrating how a set of focal displacements 1204 can be generated from a set of transchannel intensity slopes 902 according to one or more embodiments described herein.

[0116] As shown in the figure, a set of focal displacements 1204 can correspond to a set of transchannel intensity slopes 902 (e.g., in a one-to-one manner). Therefore, since a set of transchannel intensity slopes 902 can include n slopes, a set of focal displacements 1204 can include n displacements: focal displacement 1 to focal displacement n. In other words, each transchannel intensity slope can have one focal displacement.

[0117] For example, the focal displacement 1 may correspond to the intensity slope 1 across the channel. That is, the displacement component 124 can electronically calculate the focal displacement 1 by feeding the intensity slope 1 across the channel to the slope-displacement transfer function 1202. Furthermore, since the focal displacement 1 may correspond to the intensity slope 1 across the channel, and since the intensity slope 1 across the channel may correspond to the gantry angle 1, the focal displacement 1 may be considered to correspond to the gantry angle 1. In various cases, the focal displacement 1 may be a scalar representing a distance along any suitable axis and / or direction that separates the focal position when the X-ray tube 106 is positioned according to the gantry angle 1 from the desired and / or predetermined focal position. In other words, the focal displacement 1 may represent how far (e.g., in micrometers) the focal point is from its desired / predetermined position when the X-ray tube 106 is positioned at the gantry angle 1.

[0118] Similarly, the focal displacement n can correspond to the transchannel intensity slope n. That is, the displacement component 124 can electronically calculate the focal displacement n by feeding the transchannel intensity slope n into the slope-displacement transfer function 1202. As mentioned above, because the focal displacement n can correspond to the transchannel intensity slope n, and because the transchannel intensity slope n can correspond to the gantry angle n, the focal displacement n can be considered to correspond to the gantry angle n. In various cases, the focal displacement n can be a scalar representing a distance along any suitable axis and / or direction that separates the focal position when the X-ray tube 106 is positioned according to the gantry angle n from the desired and / or predetermined focal position. In other words, the focal displacement n can represent how far (e.g., in micrometers) the focal point is from its desired / predetermined position when the X-ray tube 106 is positioned at the gantry angle n.

[0119] Therefore, since the X-ray tube 106 can sweep across a set of gantry angles 402 during scanning (e.g., during an air scan caused by the scanning component 116), and since a set of focal displacements 1204 can each correspond to a set of gantry angles 402, the set of focal displacements 1204 can be regarded as indicating, representing, and / or otherwise conveying the intra-scan movement of the focal point of the medical scanner 104 (e.g., can be regarded as showing how the focal point moves along any suitable axis / dimension when the X-ray tube 106 rotates around / along the gantry 108).

[0120] Figure 14 A block diagram of an exemplary, non-limiting system 1400 comprising a set of electronic actions is shown, which facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein. As shown, in some cases, system 1400 may include the same components as system 1200 and may also include a set of electronic actions 1402.

[0121] In various embodiments, the actuating component 126 may electronically perform, induce, initiate, and / or otherwise facilitate a set of electronic actions 1402 based on a set of focal displacements 1204. In various aspects, the set of electronic actions 1402 may include any suitable number of actions relating to and / or otherwise involving the set of focal displacements 1204.

[0122] As a non-limiting example, a set of electronic actions 1402 may include visually plotting, depicting, and / or rendering a set of focal displacements 1204 relative to a set of gantry angles 402 on any suitable electronic display, screen, and / or monitor (not shown). In this case, the set of gantry angles 402 may be plotted / depicted along the horizontal axis, and / or the set of focal displacements 1204 may be plotted / depicted along the vertical axis. In various respects, medical professionals and / or technical experts may visually view and / or visually examine such graphs / charts to see how the focus of the medical scanner 104 moves and / or changes position as the X-ray tube 106 rotates about / along the gantry 108.

[0123] As another non-limiting example, a set of electronic actions 1402 may include comparing a set of focal displacements 1204 with any suitable threshold, and / or generating / transmitting a recommendation to any suitable computing device (not shown) based on such comparison. For example, execution element 126 may electronically compare each focal displacement in the set of focal displacements 1204 with a maximum permissible displacement threshold. If any focal displacement in the set of focal displacements 1204 exceeds the maximum permissible displacement threshold, execution element 126 may electronically generate and / or transmit a message to any suitable computing device (not shown), wherein such a message recommends and / or requests technical maintenance and / or repair to be performed on the medical scanner 104. In contrast, if none of the focal displacements in the set of focal displacements 1204 exceeds the maximum permissible displacement threshold, execution element 126 may electronically generate and / or transmit a message to any suitable computing device (not shown), wherein such a message indicates that technical maintenance and / or repair is not yet required on the medical scanner 104.

[0124] To help clarify the various details mentioned above, please consider Figures 15 to 17 . Figures 15 to 17 Non-limiting, exemplary figures 1500, 1600, and 1700 are shown according to one or more embodiments described herein.

[0125] In various aspects, the inventors have simplified the non-limiting embodiments described herein to practice, wherein the medical scanner 104 performs an air scan including 984 gantry angles, and wherein the detector 110 has more than 800 channels. In various cases, the graphic 1500 visually illustrates in grayscale a set of row average intensity value vectors 602 for this non-limiting embodiment. As shown, 984 gantry angles (e.g., in Figure 15 Each rack angle in the view (referred to as "view") can have a corresponding vector of row average intensity values, where each vector of row average intensity values ​​has more than 800 elements (e.g., one element per channel of detector 110). In various cases, graph 1600 visually illustrates a set of cross-channel intensity slopes 902 for this non-limiting embodiment. As shown, each rack angle in the 984 rack angles (e.g., again referred to as "view") can have a corresponding cross-channel intensity slope. Although not in... Figure 16 It is clearly shown in the text, but the intensity slope of each cross-channel can be considered as having The unit is . In various respects, Figure 1700 visually illustrates a set of focal displacements 1204 for this non-limiting embodiment. As shown, each of the 984 rack angles (e.g., again referred to as "views") may have a corresponding focal displacement value, which can be obtained by applying the slope-displacement transfer function 1202 to the corresponding cross-channel strength slope of that rack angle (e.g., that of the view).

[0126] As described herein, a set of focal displacements 1204 that describe / represent the intra-scan motion of the focal spot of the medical scanner 104 can be calculated by feeding a set of transchannel intensity slopes 902 into the slope-displacement transfer function 1202. Therefore, to facilitate this calculation, the slope-displacement transfer function 1202 should first be obtained. As mentioned above, the slope-displacement transfer function 1202 can be any suitable mathematical function and / or combination of mathematical functions that can take the transchannel intensity slopes (and / or variations in the transchannel intensity slopes) as input variables and produce focal displacement values ​​as outputs. The specific functions (e.g., polynomial, sine, logarithmic, exponential) and / or coefficient values ​​constituting and / or included in the slope-displacement transfer function 1202 can vary depending on the characteristics of the medical scanner 104. In other words, there may not be a universal form for the slope-displacement transfer function 1202. However, regardless of the characteristics of the medical scanner 104, as referenced... Figures 18 to 20 The slope-displacement transfer function 1202 described herein can be generally derived and / or obtained.

[0127] Figures 18 to 20Flowcharts are shown of exemplary, non-limiting computer-implemented methods 1800, 1900, and 2000 for generating slope-displacement transfer functions according to one or more embodiments described herein.

[0128] First, consider the computer-implemented method 1800. In various embodiments, action 1802 may include a medical scanner (e.g., 104) accessing a desired slope-displacement transfer function (e.g., 1202).

[0129] In various aspects, action 1804 may include calculating the baseline cross-channel slope for the medical scanner. In various cases, this may be achieved as follows. First, the medical scanner may perform a partial air scan at any single gantry angle (e.g., a full air scan may sweep across multiple gantry angles, while a partial air scan may be performed at one gantry angle). The result of such a partial air scan may be a single intensity value matrix recorded by the medical scanner's multi-channel, multi-row detectors (e.g., 110). This intensity value matrix may be referred to as an air-based intensity value matrix. Then, as referenced above... Figures 6 to 8 The row average of the air-based intensity value matrix is ​​performed to produce an intensity value vector. This intensity value vector may be referred to as an air-based intensity value vector (e.g., an air-based row-averaged intensity value vector). Finally, a linear trend line and / or a best-fit line can be fitted to the air-based intensity value vector, as referenced above. Figures 9 to 11 The slope of this linear trend line and / or the slope of this best-fit line can be considered as the baseline slope across the channel.

[0130] In various cases, action 1806 may include calculating the baseline focal position corresponding to the baseline cross-channel slope. In various cases, this may be achieved as follows: First, a medical scanner may be used to perform a partial edge scan at the same gantry angle used to calculate the baseline cross-channel slope (e.g., a full edge scan may sweep across multiple gantry angles, while a partial edge scan may be performed at one gantry angle). The result of such a partial edge scan may be a single intensity value matrix recorded by a multi-channel, multi-row detector (e.g., 110) of the medical scanner. This intensity value matrix may be referred to as the edge-based intensity value matrix. Next, the edge-based intensity value matrix may be normalized via element-wise division with the air-based intensity value matrix. The result of this normalization may be referred to as the normalized edge-based intensity value matrix. Finally, a line spread function and / or an approximate point spread function may be derived from the normalized edge-based intensity value matrix. Those skilled in the art will understand how the line spread function and / or point spread function are derived in this manner. In various cases, the location of the centroid of the point spread function may be considered as the baseline focal position.

[0131] As shown in the figure, the computer-implemented method 1800 can then proceed to action 1902 of the computer-implemented method 1900.

[0132] In various embodiments, action 1902 may include calculating the cross-channel slope of the perturbation for the medical scanner. In various cases, this may be achieved as follows: First, a known positional offset may be injected into the medical scanner (e.g., the anode and / or cathode of the X-ray tube of the medical scanner may be offset relative to each other by any suitable known amount). Then, the medical scanner may perform a partial air scan after the injection of the known positional offset and at the same gantry angle used to calculate the baseline cross-channel slope. The result of this partial air scan may be a single intensity value matrix recorded by the multi-channel, multi-row detectors of the medical scanner. This intensity value matrix may be referred to as the air-based intensity value matrix of the perturbation. Then, as referenced above... Figures 6 to 8 The row average of the air-based intensity value matrix of the disturbance is performed to produce an intensity value vector. This intensity value vector may be referred to as the air-based intensity value vector of the disturbance (e.g., the row-averaged intensity value vector of the disturbance). Finally, a linear trend line and / or a best-fit line can be fitted to the air-based intensity value vector of the disturbance, as referenced above. Figures 9 to 11 The slope of this linear trend line and / or the slope of this best-fit line can be considered as the slope of the perturbation across the channel.

[0133] In various aspects, action 1904 may include calculating the focal location of the perturbation corresponding to the cross-channel slope of the perturbation. In various cases, this may be achieved as follows: First, the medical scanner may perform a partial edge scan after injecting a known positional offset and at the same gantry angle used to calculate the baseline cross-channel slope. The result of this partial edge scan may be a single intensity value matrix recorded by the multi-channel, multi-row detector of the medical scanner. This intensity value matrix may be referred to as the edge-based intensity value matrix of the perturbation. Next, the edge-based intensity value matrix of the perturbation may be normalized via element-wise division with the air-based intensity value matrix of the perturbation. The result of this normalization may be referred to as the normalized edge-based intensity value matrix of the perturbation. Finally, a line spread function and / or an approximate point spread function may be derived from the normalized edge-based intensity value matrix of the perturbation. Again, those skilled in the art will understand how the line spread function and / or point spread function are derived in this manner. In various cases, the location of the centroid of such point spread function may be considered as the focal location of the perturbation.

[0134] In various cases, action 1906 may include determining whether the focal positions of w perturbations and the cross-channel slopes of w perturbations have been calculated, supporting any suitable positive integer w. If not, the computer-implemented method 1900 may return to action 1902. If yes, the computer-implemented method 1900 may proceed to action 2002 of the computer-implemented method 2000. (As from...) Figure 19 As can be seen, actions 1902 through 1906 can be iterated until the focal position of w for the perturbation and the cross-channel slope of the perturbation have been calculated. In other words, actions 1902 through 1906 can be iterated until w known positional offsets (e.g., which may all be different from each other) have been injected into the medical scanner.

[0135] Now, consider a computer-implemented method 2000. In various embodiments, action 2002 may include calculating w focal displacements by subtracting the baseline focal position (e.g., calculated at action 1806) from the focal position of each of the w perturbations (e.g., calculated at action 1904).

[0136] In various aspects, action 2004 may include calculating w variations of the cross-channel slope by subtracting the baseline cross-channel slope (e.g., calculated at action 1804) from the cross-channel slope of each of the w perturbations (e.g., calculated at action 1902).

[0137] In various cases, action 2006 may include drawing w focus displacements for w changes in the cross-channel slope.

[0138] In various cases, action 2008 may include fitting a trend line (e.g., linear, quadratic, polynomial, exponential, logarithmic, sine) to the graph. In various cases, such a trend line may be considered as a slope-displacement transfer function. In this case, the focal displacement when given the cross-channel slope of a medical scanner (e.g., one of 902) is calculated by subtracting the baseline cross-channel slope from this given cross-channel slope (e.g., calculated at action 1804); and feeding this difference to the trend line (e.g., feeding it to the slope-displacement transfer function).

[0139] in any case, Figures 18 to 20 The paper explains how the slope-displacement transfer function 1202 for the medical scanner 104 can be obtained experimentally.

[0140] In various implementations, a particular function and / or coefficient of the slope-displacement transfer function 1202 may depend on various configurable and / or controllable settings / parameters of the medical scanner 104. For example, the slope-displacement transfer function 1202 may depend on the anode-cathode voltage and / or current intensity of the medical scanner 104, the type of filter of the medical scanner 104 (e.g., planar filter vs. butterfly filter), and / or the size of the focal spot of the medical scanner 104 (e.g., measured in micrometers and / or millimeters). Thus, in various cases, a unique slope-displacement transfer function is obtained for each unique combination of controllable parameters / settings of the medical scanner 104 (e.g., a first slope-displacement transfer function is obtained when the medical scanner 104 is configured to use a first anode-cathode voltage / current intensity, a first filter, and / or a first focal spot size; a second slope-displacement transfer function is obtained when the medical scanner 104 is configured to use a second anode-cathode voltage / current intensity, a second filter, and / or a second focal spot size). Therefore, in various cases, the computer-implemented method 1800-2000 can be repeated for each unique combination of configurable parameters of the medical scanner 104.

[0141] In some cases, a set of slope-displacement transfer functions may be available and / or accessible for displacement component 124 (e.g., due to...). Figures 18 to 20 (repeated specific implementation), and the displacement component 124 can select the slope-displacement transfer function 1202 from a set based on specific and / or currently configurable parameters of the medical scanner 104.

[0142] Figure 21 A flowchart is shown of an exemplary, non-limiting computer-implemented method 2100 that facilitates low-cost estimation and / or tracking of intra-scan focal displacement according to one or more embodiments described herein. In various cases, the intra-scan focal tracking system 102 facilitates the computer-implemented method 2100.

[0143] In various embodiments, action 2102 may include a device operatively coupled to the processor (e.g., via 116) causing a medical imaging scanner (e.g., 104) to perform an air scan, wherein the medical imaging scanner has an X-ray tube (e.g., 106), a gantry (e.g., 108), and / or a multi-channel, multi-row detector (e.g., 110).

[0144] In various aspects, action 2104 may include access by a device (e.g., via 118) to data generated by a medical imaging scanner and associated with an air scan (e.g., 302). In various cases, this data may include a set of gantry angles scanned by the X-ray tube during the air scan (e.g., 402). Furthermore, this data may include a matrix of intensity values ​​recorded by a multi-channel, multi-row detector during the air scan (e.g., 404). In various cases, the matrix of intensity values ​​may correspond to a set of gantry angles respectively.

[0145] In various cases, action 2106 may include the calculation of a set of cross-channel strength slopes (e.g., 902) by the device (e.g., via 122) based on a set of strength value matrices. In various cases, the set of cross-channel strength slopes may correspond to a set of rack angles respectively.

[0146] In various aspects, action 2108 may include applying a slope-displacement transfer function (e.g., 1202) to a set of cross-channel strength slopes by a device (e.g., via 124) to produce a set of focal displacements (e.g., 1204) corresponding to a set of rack angles respectively.

[0147] In various cases, 2110 may include one or more electronic actions (e.g., 1402) initiated by a device (e.g., via 126) based on a set of focal displacements.

[0148] Although not in Figure 21 As explicitly stated, but one or more electronic actions may include drawing a set of focal displacements (e.g., via 126) on an electronic display for a set of rack angles (e.g., as referenced). Figure 17 (As shown).

[0149] Although not in Figure 21 As explicitly stated, one or more electronic actions may include, in response to determining that a set of focus displacements has failed to meet at least one threshold, a recommendation that the medical imaging scanner should be maintained by the device (e.g., via 126).

[0150] Although not in Figure 21 The text explicitly states that, however, the computer-implemented method 2100 may further include: calculating a set of row average intensity value vectors (e.g., 602) by a device (e.g., via 120) based on a set of intensity value matrices, wherein the set of row average intensity value vectors may each correspond to a set of rack angles. In various cases, calculating a set of cross-channel intensity slopes may be based on applying a trendline technique to a set of row average intensity value vectors across the cross-channel intervals (e.g., as referenced). Figures 9 to 11 (The explanation is missing).

[0151] Although not in Figure 21As explicitly shown, but the computer-implemented method 2100 may also include selecting a slope-displacement transfer function from a set of available transfer functions by a device (e.g., via 124) based on one or more configurable parameters of a medical imaging scanner. In various cases, one or more configurable parameters may include the anode-cathode voltage of the X-ray tube, the anode-cathode current of the X-ray tube, the filter type of the X-ray tube, and / or the focal size of the X-ray tube.

[0152] Although not in Figure 21 The text explicitly states that, however, the slope-displacement transfer function can be estimated based on multiple focal position perturbations injected into the X-ray tube (e.g., as referenced). Figures 18 to 20 (The explanation is missing).

[0153] Therefore, the various embodiments described herein include computerized tools that can estimate and / or track the intra-scan motion of a medical scanner's focus in a low-cost and / or low-burden manner by utilizing cross-channel intensity slope. This technique can be considered far more efficient than performing tungsten edge scanning at every possible gantry angle of the medical scanner. Therefore, such computerized systems qualify as useful and practical applications of computers.

[0154] In various contexts, machine learning algorithms and / or models may be implemented in any suitable manner to facilitate any suitable aspect described herein. To facilitate some of the machine learning aspects described above in the various implementations of the invention of this subject, the following discussion of artificial intelligence (AI) is considered. Various implementations of the invention of this subject may employ artificial intelligence to facilitate the automation of one or more features of the invention. These components may employ various AI-based schemes to perform the various implementations / examples disclosed herein. To provide or contribute to the numerous determinations of the invention (e.g., determination, detection, inference, computation, prediction, prognosis, estimation, derivation, forecasting, detection, estimation), components of the invention may examine the whole or a subgroup of data to which they have been granted access and may provide inference about or determine the state of the system and / or environment from a set of observations captured via events and / or data. For example, determination may be used to identify a particular context or action, or a probability distribution of states may be generated. These determinations may be probabilistic; that is, the computation of the probability distribution of states of interest is based on consideration of data and events. Determination may also refer to techniques used to compose higher-level events from a set of events and / or data.

[0155] This determination can lead to the construction of new events or actions from a set of observed events and / or stored event data, regardless of whether the events are closely related in time, and regardless of whether the events and data come from one or more event and data sources. The components disclosed herein can be combined to perform automated and / or determined actions related to the claimed subject matter using various classification schemes (explicitly trained (e.g., via training data) and implicitly trained (e.g., via observed behavior, preferences, historical information, received external information, etc.)) and / or systems (e.g., support vector machines, neural networks, expert systems, Bayesian confidence networks, fuzzy logic, data fusion engines, etc.). Therefore, classification schemes and / or systems can be used to automatically learn and perform various functions, actions, and / or determinations.

[0156] The classifier can take the input attribute vector z = (z1, z2, z3, z4, z5) as input. n This maps the input to a confidence level that it belongs to a certain category, as shown by f(z) = confidence level (category). Such classification can employ probability- and / or statistical analyses (e.g., analyzing utility and cost considerations) to determine the actions to be automated. Support Vector Machines (SVMs) are an example of classifiers that can be used. SVMs operate by finding a hypersurface in the space of possible inputs, where the hypersurface attempts to separate triggering criteria from non-triggering events. Intuitively, this makes the classification correct for test data that is close to but different from the training data. Other directed and undirected model classification methods include, for example, Naive Bayes, Bayesian networks, decision trees, neural networks, fuzzy logic models, and can employ any of the probabilistic classification models that provide different independent patterns. Classification, as used in this paper, also includes statistical regression for developing priority models.

[0157] Those skilled in the art will understand that the disclosure herein describes non-limiting examples of various embodiments of the present invention. For ease of description and / or illustration, the term "each" is used in various parts of the disclosure when discussing various embodiments of the present invention. Those skilled in the art will understand that such use of the term "each" is a non-limiting example. In other words, when the disclosure herein provides a description applicable to "each" of a particular object and / or component, it should be understood that this is a non-limiting example of various embodiments of the present invention, and it should also be understood that in various other embodiments of the present invention, such a description may apply to fewer than "each" of the particular object and / or component.

[0158] To provide additional context for the various implementation schemes described herein Figure 22The following discussion aims to provide a brief general description of a suitable computing environment 2200 for various implementations of the embodiments described herein. While the embodiments have been described above in the general context of computer-executable instructions that can run on one or more computers, those skilled in the art will recognize that these embodiments may also be implemented in combination with other program modules and / or as a combination of hardware and software.

[0159] Typically, program modules include routines, programs, components, data structures, etc., that perform specific tasks or implement specific abstract data types. Furthermore, those skilled in the art will understand that the methods of this invention can be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframe computers, Internet of Things (IoT) devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, each operatively coupled to one or more associated devices.

[0160] The embodiments illustrated in this paper can also be practiced in a distributed computing environment where specific tasks are performed by remote processing devices linked via a communication network. In a distributed computing environment, program modules can reside in both local and remote memory storage devices.

[0161] Computing devices typically include a variety of media, which may include computer-readable storage media, machine-readable storage media, and / or communication media, wherein the two terms are used interchangeably herein, as described below. A computer-readable storage medium or a machine-readable storage medium can be any available storage medium accessible by a computer, and includes volatile and non-volatile media, removable and non-removable media. By way of example and not limitation, a computer-readable storage medium or a machine-readable storage medium can be implemented in conjunction with any method or technique for storing information such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0162] Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, optical disc read-only memory (CDROM), DVD, Blu-ray disc (BD) or other optical disc storage devices, magnetic tape cassettes, magnetic tape, disk storage devices or other magnetic storage devices, solid-state drives or other solid-state storage devices, or other tangible and / or non-transitory media that can be used to store desired information. In this regard, the terms “tangible” or “non-transitory” used herein to describe storage devices, memories, or computer-readable media should be understood to exclude only the propagation of transient signals themselves as a modifier, and do not waive the rights of all standard storage devices, memories, or computer-readable media that do not only propagate transient signals themselves.

[0163] Computer-readable storage media can be accessed by one or more local or remote computing devices, for example, through access requests, queries or other data retrieval protocols, to perform various operations on the information stored on the media.

[0164] Communication media typically contain computer-readable instructions, data structures, program modules, or other structured or unstructured data in a data signal. This data signal can be a modulated data signal, such as a carrier wave or other transmission mechanism, and includes any information transmission or delivery medium. The terms "modulated data signal" or "signal" refer to a signal whose one or more characteristics are set or altered to encode information in one or more signals. By way of example and not limitation, communication media include wired media, such as wired networks or direct wired connections, and wireless media, such as acoustic, RF, infrared, and other wireless media.

[0165] Refer again Figure 22 An exemplary environment 2200 for implementing various embodiments of the aspects described herein includes a computer 2202, which includes a processing unit 2204, system memory 2206, and a system bus 2208. The system bus 2208 connects system components, including but not limited to the system memory 2206, to the processing unit 2204. The processing unit 2204 can be any of a variety of commercially available processors. Dual-microprocessor and other multiprocessor architectures may also be used as the processing unit 2204.

[0166] System bus 2208 can be any of several types of bus architectures that can be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. System memory 2206 includes ROM 2210 and RAM 2212. The basic input / output system (BIOS) can be stored in non-volatile memory such as ROM, erasable programmable read-only memory (EPROM), or EEPROM, wherein the BIOS contains basic routines that facilitate, for example, the transfer of information between components within computer 2202 during startup. RAM 2212 may also include high-speed RAM, such as static RAM for caching data.

[0167] Computer 2202 also includes an internal hard disk drive (HDD) 2214 (e.g., EIDE, SATA), one or more external storage devices 2216 (e.g., floppy disk drive (FDD) 2216, memory stick or flash drive reader, memory card reader, etc.), and drives 2220, such as solid-state drives or optical disc drives, which can read from or write to disks 2222 (e.g., CD-ROM, DVD, BD, etc.). Alternatively, in cases involving solid-state drives, disks 2222 are not included unless separate. Although the internal HDD 2214 is shown as residing within computer 2202, the internal HDD 2214 may also be configured for external use in a suitable infrastructure (not shown). Additionally, although not shown in environment 2200, solid-state drives (SSDs) may be used as a supplement to or alternative to HDD 2214. HDD 2214, external storage device 2216, and drive 2220 can be connected to system bus 2208 via HDD interface 2224, external storage interface 2226, and drive interface 2228, respectively. Interface 2224 for the specific implementation of the external drive may include at least one or both of Universal Serial Bus (USB) and Institute of Electrical and Electronics Engineers (IEEE) 1394 interface technologies. Other external drive connection technologies are contemplated in the embodiments described herein.

[0168] Drives and their associated computer-readable storage media provide non-volatile storage of data, data structures, computer-executable instructions, etc. For computer 2202, drives and storage media accommodate the storage of any data in a suitable digital format. Although the above description of computer-readable storage media refers to a corresponding type of storage device, those skilled in the art will understand that other types of computer-readable storage media (whether currently existing or developed in the future) can also be used in the exemplary operating environment, and furthermore, any such storage media may contain computer-executable instructions for performing the methods described herein.

[0169] Multiple program modules may be stored in the drive and RAM 2212, including an operating system 2230, one or more application programs 2232, other program modules 2234, and program data 2236. All or part of the operating system, application programs, modules, and / or data may also be cached in RAM 2212. The systems and methods described herein can be implemented using various commercially available operating systems or combinations of operating systems.

[0170] Computer 2202 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediary may emulate the hardware environment used for operating system 2230, and the emulated hardware may optionally be different from that of operating system 2230. Figure 22 The hardware is shown. In such implementations, the operating system 2230 may include one of a plurality of virtual machines (VMs) hosted at the computer 2202. Furthermore, the operating system 2230 may provide a runtime environment for the application 2232, such as the Java Runtime Environment or the .NET Framework. A runtime environment is a compatible execution environment that allows the application 2232 to run on any operating system that includes a runtime environment. Similarly, the operating system 2230 may support containers, and the application 2232 may take the form of a container, which is a lightweight, standalone, executable software package that includes, for example, code, runtime, system tools, system libraries, and settings for the application.

[0171] Furthermore, computer 2202 can be enabled using security modules such as Trusted Processing Module (TPM). For example, in the case of TPM, the boot part is hashed in the next boot part and waits for the result to be matched with a security value before loading the next boot part. This process can occur at any layer of the computer 2202's code execution stack, such as at the application execution level or the operating system (OS) kernel level, thereby achieving security at any code execution level.

[0172] Users can input commands and information into computer 2202 through one or more wired / wireless input devices (e.g., keyboard 2238, touchscreen 2240, and pointing devices such as mouse 2242). Other input devices (not shown) may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls or other remote controls, joysticks, virtual reality controllers and / or virtual reality headsets, gamepads, styluses, image input devices (e.g., cameras), gesture sensor input devices, visual motion sensor input devices, emotion or face detection devices, biometric input devices (e.g., fingerprint or iris scanners), etc. These and other input devices are typically connected to processing unit 2204 via input device interface 2244, which can be connected to system bus 2208, but these and other input devices can be connected via other interfaces, such as parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, etc. Interfaces, etc.

[0173] Monitor 2246 or other types of display devices may also be connected to system bus 2208 via an interface (such as video adapter 2248). In addition to monitor 2246, computers typically include other peripheral output devices (not shown), such as speakers, printers, etc.

[0174] Computer 2202 can operate in a networked environment using logical connections to one or more remote computers (such as remote computer 2250) via wired and / or wireless communications. Remote computer 2250 can be a workstation, server computer, router, personal computer, laptop computer, microprocessor-based entertainment device, peer-to-peer device, or other public network node, and typically includes many or all of the elements described relative to computer 2202, but for simplicity, only memory / storage device 2252 is shown. The depicted logical connections include wired / wireless connections to a local area network (LAN) 2254 and / or a larger network (e.g., a wide area network (WAN) 2256). Such LAN and WAN networking environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which can connect to global communication networks, such as the Internet.

[0175] When used in a LAN networking environment, computer 2202 can connect to local network 2254 via a wired and / or wireless communication network interface or adapter 2258. Adapter 2258 facilitates wired or wireless communication with LAN 2254, which may also include a wireless access point (AP) configured thereon for communicating with adapter 2258 in wireless mode.

[0176] When used in a WAN networking environment, computer 2202 may include modem 2260 or may be connected to a communication server on WAN 2256 via other means (such as via the Internet) for establishing communication over WAN 2256. Modem 2260 (which may be internal or external and wired or wireless) may be connected to system bus 2208 via input device interface 2244. In a networking environment, program modules depicted relative to computer 2202 or parts thereof may be stored in remote memory / storage device 2252. It should be understood that the network connection shown is an example, and other means for establishing communication links between computers may be used.

[0177] When used in a LAN or WAN networking environment, in addition to or as an alternative to the external storage device 2216 described above, computer 2202 can access cloud storage systems or other network-based storage systems, such as, but not limited to, network virtual machines that provide one or more aspects of information storage or processing. Generally, the connection between computer 2202 and the cloud storage system can be established, for example, via adapter 2258 or modem 2260 through LAN 2254 or WAN 2256. When computer 2202 is connected to the associated cloud storage system, external storage interface 2226 can manage the storage provided by the cloud storage system by means of adapter 2258 and / or modem 2260, just like other types of external storage devices. For example, external storage interface 2226 can be configured to provide access to cloud storage sources as if these sources were physically connected to computer 2202.

[0178] Computer 2202 is operable to communicate with any wirelessly operated device or entity located wirelessly, such as a printer, scanner, desktop and / or laptop computer, portable data assistant, communications satellite, or any equipment or location associated with a wirelessly detectable tag (e.g., a self-service machine, newsstand, store shelf, etc.). This may include Wi-Fi and Wireless technology. Therefore, communication can be a predefined structure like a regular network, or simply self-organizing communication between at least two devices.

[0179] Figure 23This is a schematic block diagram of a sample computing environment 2300 with which the disclosed subject matter can interact. The sample computing environment 2300 includes one or more clients 2310. Clients 2310 can be hardware and / or software (e.g., threads, processes, computing devices). The sample computing environment 2300 also includes one or more servers 2330. Servers 2330 can also be hardware and / or software (e.g., threads, processes, computing devices). For example, server 2330 can accommodate threads to perform transformations by employing one or more embodiments described herein. One possible communication between client 2310 and server 2330 can be in the form of data packets suitable for transmission between two or more computer processes. The sample computing environment 2300 includes a communication framework 2350 that can be used to facilitate communication between client 2310 and server 2330. Client 2310 is operatively connected to one or more client data repositories 2320, which can be used to store information local to client 2310. Similarly, server 2330 is operatively connected to one or more server data repositories 2340, which can be used to store information locally on server 2330.

[0180] The various embodiments described herein can be systems, methods, apparatuses, and / or computer program products at any possible level of integrated technical detail. Computer program products may include computer-readable storage media (or media having computer-readable program instructions thereon for causing a processor to perform aspects of the various embodiments described herein. Computer-readable storage media can be tangible devices that can hold and store instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A less complete list of more specific examples of computer-readable storage media may also include: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable optical disc read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanical encoding devices (such as punch cards or raised structures in grooves on which instructions are recorded), and any suitable combination of the foregoing. As used herein, a computer-readable storage medium should not be construed as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses passing through fiber optic cables), or electrical signals transmitted through wires.

[0181] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device, or downloaded to an external computer or external storage device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network). The network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them for storage in a computer-readable storage medium within the corresponding computing / processing device. The computer-readable program instructions used to perform the operations of the various embodiments described herein may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages ​​(including object-oriented programming languages ​​such as Smalltalk, C++, etc.) and procedural programming languages ​​(such as the "C" programming language or similar programming languages). Computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet through an Internet service provider). In some implementations, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute computer-readable program instructions to personalize the electronic circuitry by utilizing state information of the computer-readable program instructions in order to perform aspects of the various implementations described herein.

[0182] This document describes aspects of various embodiments of the invention with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. These computer-readable program instructions can also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer-readable storage medium having the instructions stored therein includes an article of manufacture comprising instructions implementing aspects of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus or other equipment to cause a series of operations to be performed on the computer, other programmable apparatus or other equipment to produce a computer-implemented process, such that the instructions that execute on the computer, other programmable apparatus or other equipment implement the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0183] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments described herein. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions indicated in the blocks may not occur in the order shown in the figures. For example, two blocks shown consecutively may actually be executed substantially simultaneously, or sometimes they may be executed in reverse order, depending on the functionality involved. It will also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified function or action or implements a combination of dedicated hardware and computer instructions.

[0184] Although the subject matter has been described above in the general context of computer executable instructions of a computer program product running on one or more computers, those skilled in the art will recognize that the present disclosure may also be implemented, or may be implemented in combination with other program modules. Generally, program modules include routines, programs, components, data structures, etc., that perform specific tasks and / or implement specific abstract data types. Furthermore, those skilled in the art will understand that the computer implementation of the present invention can be practiced using other computer system configurations, including single-processor or multi-processor computer systems, small computing devices, mainframe computers, and computers, handheld computing devices (e.g., PDAs, telephones), microprocessor-based or programmable consumer or industrial electronic devices, etc. The illustrated aspects can also be practiced in a distributed computing environment in which tasks are performed by remote processing devices linked via a communication network. However, some (if not all) aspects of the present disclosure can be practiced on a standalone computer. In a distributed computing environment, program modules may reside in both local and remote memory storage devices.

[0185] As used herein, the terms “component,” “system,” “platform,” “interface,” etc., may refer to and / or include computer-related entities or entities associated with an operator having one or more specific functions. Entities disclosed herein may be hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to, a program running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. By way of illustration, an application running on a server and a server may both be components. One or more components may reside within a program and / or an execution thread, and components may be located on a single computer and / or distributed across two or more computers. Furthermore, a corresponding component may execute on various computer-readable media on which various data structures are stored. Components may communicate via local and / or remote processes, such as based on signals having one or more data packets (e.g., data from one component that interacts with another component in a local system, a distributed system, and / or a network (such as the Internet with other systems). For example, a component can be a device having specific functions provided by mechanical parts operated by an electrical or electronic circuitry system, which is operated by software or firmware applications executed by a processor. In such cases, the processor may be internal or external to the device and may execute at least a portion of the software or firmware application. As yet another example, a component can be a device that provides specific functions through electronic components rather than mechanical parts, wherein the electronic components may include a processor or other means for executing software or firmware that at least partially gives the electronic components functionality. In one aspect, a component may be emulated via a virtual machine, for example, within a cloud computing system.

[0186] Furthermore, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X adopts A or B" is intended to mean any natural inclusive substitution. That is, if X adopts A; X adopts B; or X adopts both A and B, then "X adopts A or B" is satisfied in any of the foregoing cases. Additionally, unless otherwise specified or clear from the context to be directed to the singular form, the articles "a" and "an" used in this specification and accompanying drawings should generally be understood to mean "one or more." As used herein, the terms "example" and / or "exemplary" are used to indicate what is intended as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited to such examples. Furthermore, any aspect or design described herein as "example" and / or "exemplary" should not be construed as preferred or advantageous over other aspects or designs, nor does it exclude equivalent exemplary structures and techniques known to those skilled in the art.

[0187] As used herein, the term "processor" can refer substantially to any computing processing unit or device, including but not limited to a single-core processor; a single processor with software multithreading capabilities; a multi-core processor; a multi-core processor with software multithreading capabilities; a multi-core processor with hardware multithreading technology; a parallel platform; and a parallel platform with distributed shared memory. Additionally, a processor can refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. Furthermore, a processor can utilize nanoscale architectures (such as, but not limited to, molecular and quantum dot-based transistors, switches, and gates) to optimize space usage or enhance the performance of user equipment. A processor can also be implemented as a combination of computing processing units. In this disclosure, terms such as "repository," "storage device," "data repository," "data storage device," "database," and substantially any other information storage component related to the operation and function of a component are used to refer to a "memory component," an entity specifically embodied in "memory," or a component including memory. It should be understood that the memory and / or memory components described herein may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. By way of illustration and not limitation, non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, or non-volatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)). For example, volatile memory may include RAM that can act as external cache memory. By way of illustration and not limitation, RAM can be provided in a variety of forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM). Furthermore, the memory components disclosed in the systems or computer-implemented methods described herein are intended to include, but are not limited to, these and any other suitable types of memory.

[0188] The foregoing description includes only examples of systems and computer-implemented methods. Of course, it is impossible to describe every conceivable combination of components or computer-implemented methods for the purposes of describing this disclosure, but those skilled in the art will recognize that many other combinations and substitutions of this disclosure are possible. Furthermore, regarding the extent to which the terms “comprising,” “having,” “possessing,” etc., are used in the detailed description, claims, appendices, and drawings, such terms are intended to be inclusive in a manner similar to the term “comprising,” as interpreted when “comprising” is used as a transitional word in the claims.

[0189] Various embodiments have been described for illustrative purposes, but these descriptions are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best illustrate the principles of the embodiments, the practical application of or improvement of technology found in the market, or to enable others skilled in the art to understand the disclosed embodiments.

Claims

1. A system for facilitating estimation and / or tracking of in-scan focal spot displacement, the system comprising: a processor that executes computer-executable components stored in a computer- readable memory, the computer-executable components comprising: a scanning component that causes a medical imaging scanner to perform an air scan, wherein the medical imaging scanner has an x-ray tube, a gantry, and a multi-channel multi-row detector; a receiver component that accesses data produced by the medical imaging scanner and related to the air scan, wherein the data includes a set of gantry angles swept by the x-ray tube during the air scan, wherein the data includes a set of matrices of intensity values recorded by the multi-channel multi-row detector during the air scan, and wherein the set of matrices of intensity values respectively correspond to the set of gantry angles; a slope component that computes a set of cross-channel intensity slopes based on the set of matrices of intensity values, wherein the set of cross-channel intensity slopes respectively correspond to the set of gantry angles; a displacement component that applies a slope-to-displacement transfer function to the set of cross-channel intensity slopes, thereby producing a set of focal spot displacements respectively corresponding to the set of gantry angles; and an execution component that initiates one or more electronic actions based on the set of focal spot displacements.

2. The system of claim 1, wherein the one or more electronic actions include plotting the set of focal spot displacements against the set of gantry angles on an electronic display.

3. The system of claim 1, wherein the one or more electronic actions include transmitting a recommendation that the medical imaging scanner should be serviced in response to determining that the set of focal spot displacements fails to satisfy at least one threshold.

4. The system of claim 1, wherein the computer-executable components further comprise: an averaging component that computes a set of row-averaged intensity value vectors based on the set of matrices of intensity values, wherein the set of row-averaged intensity value vectors respectively correspond to the set of gantry angles, and wherein the slope component computes the set of cross-channel intensity slopes by applying a trendline technique to the set of row-averaged intensity value vectors across a channel interval.

5. The system of claim 1, wherein the displacement component selects the slope-to- displacement transfer function from a set of available transfer functions based on one or more configurable parameters of the medical imaging scanner.

6. The system of claim 5, wherein the one or more configurable parameters include an anode-cathode voltage of the x-ray tube, an anode-cathode current of the x-ray tube, a filter type of the x-ray tube, or a focal spot size of the x-ray tube.

7. The system of claim 1, wherein the slope-to-displacement transfer function is estimated based on a plurality of focal spot position perturbations injected into the x-ray tube.

8. A computer-implemented method, the computer-implemented method comprising: causessaid medical imaging scanner to perform an air scan, wherein the medical imaging scanner has an x-ray tube, a gantry, and a multi-channel multi-row detector; accesses, by the device, data generated by the medical imaging scanner and related to the air scan, wherein the data includes a set of gantry angles swept by the x-ray tube during the air scan, wherein the data includes a set of matrices of intensity values recorded by the multi-channel multi-row detector during the air scan, and wherein the set of matrices of intensity values respectively correspond to the set of gantry angles; computes, by the device, a set of cross-channel intensity slopes based on the set of matrices of intensity values, wherein the set of cross-channel intensity slopes respectively correspond to the set of gantry angles; applies, by the device, a slope-to-shift transfer function to the set of cross-channel intensity slopes, thereby generating a set of focal spot shifts respectively corresponding to the set of gantry angles; and initiates, by the device, one or more electronic actions based on the set of focal spot shifts.

9. The computer-implemented method of claim 8, wherein the one or more electronic actions include plotting, by the device and on an electronic display, the set of focal spot shifts for the set of gantry angles.

10. The computer-implemented method of claim 8, wherein the one or more electronic actions include transmitting, by the device, a recommendation that the medical imaging scanner should be serviced in response to determining that the set of focal spot shifts fails to satisfy at least one threshold.

11. The computer-implemented method of claim 8, further comprising: computes, by the device, a set of row average intensity value vectors based on the set of matrices of intensity values, wherein the set of row average intensity value vectors respectively correspond to the set of gantry angles, and wherein the set of cross-channel intensity slopes is computed based on applying a trend line technique to the set of row average intensity value vectors across channel intervals.

12. The computer-implemented method of claim 8, further comprising: selects, by the device, the slope-to-shift transfer function from a set of available transfer functions based on one or more configurable parameters of the medical imaging scanner.

13. The computer-implemented method of claim 12, wherein the one or more configurable parameters include an anode-cathode voltage of the x-ray tube, an anode-cathode current of the x-ray tube, a filter type of the x-ray tube, or a focal spot size of the x-ray tube.

14. The computer-implemented method of claim 8, wherein the slope-to-shift transfer function is estimated based on a plurality of focal spot position perturbations injected into the x-ray tube.

15. A computer program product for facilitating estimation and / or tracking of intra-scan focal spot shifts, the computer program product comprising a computer readable memory having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: cause a medical imaging scanner to perform an air scan, wherein the medical imaging scanner has an x-ray tube, a gantry, and a multi-channel multi-row detector; access data generated by the medical imaging scanner and related to the air scan, wherein the data includes a set of gantry angles swept by the x-ray tube during the air scan, wherein the data includes a set of matrices of intensity values recorded by the multi-channel multi-row detector during the air scan, and wherein the set of matrices of intensity values respectively correspond to the set of gantry angles; compute a set of cross-channel intensity slopes based on the set of matrices of intensity values, wherein the set of cross-channel intensity slopes respectively correspond to the set of gantry angles; apply a slope-to-shift transfer function to the set of cross-channel intensity slopes, thereby generating a set of focal spot shifts respectively corresponding to the set of gantry angles; and initiate one or more electronic actions based on the set of focal spot shifts. accessing data generated by the medical imaging scanner and related to the air scan, wherein the data includes a set of gantry angles swept by the X-ray tube during the air scan, wherein the data includes a set of intensity value matrices recorded by the multi-channel multi-row detector during the air scan, and wherein the set of intensity value matrices respectively correspond to the set of gantry angles; computing a set of cross-channel intensity slopes based on the set of intensity value matrices, wherein the set of cross-channel intensity slopes respectively correspond to the set of gantry angles; applying a slope-to-shift transfer function to the set of cross-channel intensity slopes, thereby generating a set of focal spot shifts respectively corresponding to the set of gantry angles; and initiating one or more electronic actions based on the set of focal spot shifts.

16. The computer program product of claim 15, wherein the one or more electronic actions include plotting the set of focal spot shifts against the set of gantry angles on an electronic display.

17. The computer program product of claim 15, wherein the one or more electronic actions include transmitting a recommendation that the medical imaging scanner be serviced in response to determining that the set of focal spot shifts fails to satisfy at least one threshold.

18. The computer program product of claim 15, wherein the program instructions are further executable to cause the processor to: compute a set of row average intensity value vectors based on the set of intensity value matrices, wherein the set of row average intensity value vectors respectively correspond to the set of gantry angles, and wherein the processor computes the set of cross-channel intensity slopes by applying a trend line technique to the set of row average intensity value vectors across channel intervals.

19. The computer program product of claim 15, wherein the program instructions are further executable to cause the processor to: select the slope-to-shift transfer function from a set of available transfer functions based on one or more configurable parameters of the medical imaging scanner.

20. The computer program product of claim 19, wherein the one or more configurable parameters include an anode-cathode voltage of the X-ray tube, an anode-cathode current of the X-ray tube, a filter type of the X-ray tube, or a focal spot size of the X-ray tube.

Images