System and method for automatically centering a phantom

Abstract

To provide a system and a method for automatically centering a phantom.SOLUTION: In one embodiment, a method for an imaging system includes acquiring scan data of a phantom, determining one or more distances from the phantom to a center of the imaging system, and automatically adjusting a position of the phantom based on the one or more distances to the center.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] FIELD OF THE INVENTION Embodiments of the subject matter disclosed herein relate to medical imaging, and more particularly to automatically centering a phantom. [Background technology]

[0002] In a computed tomography (CT) imaging system, a beam of electrons generated by a cathode is directed toward a target inside an x-ray tube. The electrons strike the target, producing a fan- or cone-shaped x-ray beam that is directed toward the object being examined (such as a patient). The x-rays, after being attenuated by the object, strike an array of radiation detectors. Each detector element generates an electrical signal, which is used to reconstruct an image of the object. Each electrical signal corresponds to a voxel / pixel in the image.

[0003] The quality of an image in terms of resolution, contrast-to-noise ratio, and other factors can depend on the alignment of each detector element in the detector array. Misalignment of detector elements can increase artifacts in the image and / or degrade image quality. A calibration process can be periodically performed on the system to acquire projection data of materials that simulate various human tissue densities. The calibration process can include performing an x-ray scanning procedure on an object called a phantom. Physical misalignment of the phantom during the calibration process can result in inaccurate calibration of the CT system. Summary of the Invention

[0004] In one embodiment, a method for an imaging system includes acquiring scan data of a phantom, determining one or more distances to a center of the phantom, and automatically adjusting a position of the phantom based on the one or more distances to the center.

[0005] It should be understood that the foregoing summary is provided to introduce in a simplified form some of the concepts that are further described in the detailed description. The foregoing summary is not intended to identify key or essential features of the claimed subject matter, the scope of which is defined uniquely by the claims. Moreover, the claimed subject matter is not limited to implementations that solve the above-described disadvantages of the present disclosure or disadvantages noted in various places in the present disclosure. [Brief explanation of the drawings]

[0006] The invention can be better understood from the following non-limiting description of examples, taken in conjunction with the drawings in which: [Figure 1] 1 shows a diagram of an imaging system according to one embodiment. [Figure 2] FIG. 1 shows a schematic block diagram of an exemplary imaging system according to one embodiment. [Figure 3] 10 is a flow chart illustrating a general method for automatically centering a phantom. [Figure 4] 1 is a flowchart illustrating a method for determining a centering distance of an imaging system according to a first embodiment. [Figure 5] This is a continuation of the flowchart in Figure 4. [Figure 6] This is a continuation of the flowchart in Figure 4. [Figure 7] 4 shows a flowchart of a method for automatically centering a phantom according to a second embodiment. [Figure 8] 1 illustrates misalignment of a first exemplary phantom. [Figure 9] 10 illustrates misalignment of a second exemplary phantom. [Figure 10] 10 illustrates a third exemplary phantom misalignment. [Figure 11] 10 is a flowchart illustrating a method for determining a centering distance of an imaging system according to a third embodiment. [Figure 12A]1 shows different angle views of the imaging system with designated points of the phantom indicated. [Figure 12B] FIG. 12B shows how the distance between the designated point and the center channel is indicated. DETAILED DESCRIPTION OF THE INVENTION

[0007] Descriptions and embodiments of the subject matter disclosed herein relate to automatically centering a phantom for calibration scans of an imaging system, such as a computed tomography (CT) system. Some imaging systems, such as a CT system or a photon-counting computed tomography (PCCT) system, may require periodic calibration (e.g., daily or weekly calibration scans) at some frequency to compensate for gain variations caused by hardware factors, such as changes in the focal position of the x-ray tube or radiation degradation of the detector. Additionally, PCCT or CT systems can acquire spectral information, which can be used to generate reference material differentiation (BMD) images. Therefore, calibrating a PCCT system may require acquiring calibration projection data that mimics the materials and material thicknesses of the human body. Therefore, phantoms for calibrating PCCT systems can include several different materials, such as polyvinyl chloride (PVC) and polyethylene (PE). Several types of phantoms, such as slab phantoms, step phantoms, and pillar phantoms, are available for calibration purposes.

[0008] Accurate calibration using a phantom depends on properly aligning the phantom. Currently, the phantom is placed in an accessory slot or on the table of the imaging system and manually aligned in a predetermined position (e.g., to the isocenter of the imaging system). For example, a user (e.g., a technician) manually aligns the phantom to the isocenter using laser guidance and scout scans with manual gantry control. However, this manual process is prone to misalignment errors and often results in additional time spent repeatedly readjusting the phantom and / or repeating imaging of the phantom if images are acquired with a misaligned phantom.

[0009] Accordingly, provided herein are systems and methods for automatically centering a phantom that at least partially address the above-mentioned problems. For example, one or more distances to the isocenter of the imaging system can be determined to determine the amount of misalignment, and therefore the amount of movement required to center the phantom. Based on the one or more distances, the imaging system can automatically move the phantom (e.g., by moving the table on which the phantom or a holder for the phantom is located) to center the phantom.

[0010] In some examples, an edge detection algorithm can be applied to determine one or more distances. For example, an edge detection algorithm can be applied to determine distances in the z direction and / or the x direction. Furthermore, in some embodiments, a tilt offset can be determined based on pixel count values ​​of acquired scan data of the phantom. The difference in pixel count values ​​between the leftmost pixel and the rightmost pixel can indicate the tilt offset. In this manner, the phantom can be automatically centered laterally, longitudinally, vertically, and rotationally based on the calculated distances and tilt. Eliminating human error in manually aligning the phantom can improve calibration accuracy. Furthermore, reducing the need for multiple manual phantom positioning and / or repeated data acquisition can save a user time.

[0011] FIG. 1 illustrates an exemplary imaging system. The illustrated imaging system may be a CT system, specifically a PCCT system 100 (also referred to as a photon-counting X-ray imaging system) configured for CT imaging using photon-counting detectors; however, it should be understood that other imaging systems (such as conventional CT systems, magnetic resonance imaging (MRI) systems, and positron emission tomography (PET) systems) may be used without departing from the scope of this disclosure. An axis system 199 is illustrated in FIG. 1 (and FIGS. 9A-10B ). The x-axis of axis system 199 may be a horizontal axis (e.g., a left-right axis), the y-axis may be a vertical axis (e.g., an axis parallel to the axis of gravity), and the z-axis may be a longitudinal axis (e.g., an axis extending into or out of the gantry).

[0012] In particular, the PCCT system 100 is configured to image a subject 112, such as a patient, an inanimate object, one or more manufactured parts, and / or a foreign object (e.g., dental implant, stent, contrast agent, etc.) within the body. The PCCT system 100 includes a gantry 102, which may further include at least one X-ray source 104 configured to emit an X-ray radiation beam 106 (see FIG. 2 ) for use in imaging the subject 112 residing on a table 114. Specifically, the X-ray source 104 is configured to emit the X-ray radiation beam 106 toward a detector array 108 located on the opposite side of the gantry 102. While a single X-ray source 104 is shown in FIG. 1 , in certain embodiments, multiple X-ray sources and multiple detectors may be used to emit multiple X-ray radiation beams and acquire projection data corresponding to the patient at the same or different energy levels. In the embodiments described herein, the X-ray detector used is a photon-counting detector capable of distinguishing between X-ray photons of different energies.

[0013] In certain embodiments, the PCCT system 100 further includes an image processor unit 110 configured to reconstruct an image of the target volume of the object 112 using an iterative image reconstruction method or an analytical image reconstruction method. For example, the image processor unit 110 may reconstruct an image of the target volume of the patient using an analytical image reconstruction method (such as filtered back projection (FBP)). In another example, the image processor unit 110 may reconstruct an image of the target volume of the object 112 using an iterative image reconstruction method (such as advanced statistical iterative reconstruction (ASIR), conjugate gradient (CG), maximum likelihood expectation maximization (MLEM), model-based iterative reconstruction (MBIR), etc.). In some examples, the image processor unit 110 may use an analytical image reconstruction method (such as FBP) in addition to the iterative image reconstruction method.

[0014] In some CT imaging system configurations, an X-ray source emits a cone-shaped beam of X-ray radiation, which is defined relative to an XYZ plane in a Cartesian coordinate system, commonly referred to as the "imaging plane." The X-ray radiation beam passes through an object (such as a patient or subject) being imaged. After being attenuated by the object, the X-ray radiation beam impinges on an array of detector elements. The intensity of the attenuated X-ray radiation beam received by the detector array depends on the attenuation of the X-ray radiation beam by the object. Each detector element in the array produces a separate electrical signal that is a measurement of the attenuation of the X-ray beam at the detector location. The attenuation measurements from all detector elements are acquired separately to generate a transmission profile.

[0015] In some CT systems, the x-ray source and detector array, along with the gantry, rotate within the imaging volume around the object being imaged, constantly changing the angle at which the x-ray beam intersects the object. A group of x-ray attenuation measurements, e.g., projection data, obtained from the detector array for one gantry angle is called a "view." A "scan" of the object involves obtaining a set of views at different gantry angles, or view angles, during one revolution of the x-ray source and detector.

[0016] FIG. 2 illustrates an exemplary imaging system 200 similar to the PCCT system 100 of FIG. 1. According to one aspect of the present disclosure, the imaging system 200 is configured to perform imaging of a subject 204 (e.g., subject 112 of FIG. 1). In a particular scan, the subject may be a phantom. The phantom may be an object configured to be scanned by a PPCT system as part of a calibration process for the PPCT system. In one embodiment, the imaging system 200 includes a detector array 108 (see FIG. 1). The detector array 108 further includes a plurality of detector elements 202 that sense an x-ray radiation beam 106 (see FIG. 2) passing through the subject 204 (e.g., a patient) to acquire corresponding projection data. In some embodiments, the detector array 108 may be fabricated in a multi-slice configuration including multiple rows of cells or detector elements 202, with one or more additional rows of detector elements 202 arranged in a parallel configuration to acquire projection data. The detector elements 202 may also be referred to as pixels or detector pixels.

[0017] In certain embodiments, the imaging system 200 may be moved to different angular positions around the object 204 to acquire desired projection data. Thus, the gantry 102 and the components mounted thereon may be configured to rotate about a center of rotation 206 to acquire projection data at different energy levels, for example. Alternatively, in embodiments where the projection angle relative to the object 204 varies over time, the mounted components may be configured to move along a general curve rather than along a portion of a circle.

[0018] As the X-ray source 104 and detector array 108 rotate, the detector array 108 collects data of the attenuated X-ray beam. The data collected by the detector array 108 is pre-processed and calibrated to adjust the data to represent the line integral of the attenuation coefficient of the object 204. The processed data is commonly referred to as a projection. In some embodiments, the individual detectors or detector elements 202 of the detector array 108 may include photon-counting detectors that record the interactions of individual photons into one or more energy bins.

[0019] The acquired set of projection data can be used for BMD. During BMD, the measured projections are converted into a set of material density projections. The material density projections can be reconstructed to form a set of material density maps (such as maps of bone, soft tissue, and / or contrast agent) or material density images for each reference material. The density maps or density images can be sequentially combined to form a 3D volumetric image of the reference materials (e.g., bone, soft tissue, and / or contrast agent) within the imaged volume.

[0020] Once reconstructed, the reference material images produced by the imaging system 200 reveal internal features of the subject 204, represented by the densities of two or more reference materials. The density images may be displayed to show these features. In traditional methods of diagnosing medical conditions (such as disease states), and more generally, medical events, a radiologist or physician examines hard copies or displays of density images to identify features of interest. Such features include lesions, the size and shape of particular anatomical structures or organs, and other features discernible from the images based on the skill and knowledge of the individual medical professional.

[0021] In one embodiment, imaging system 200 includes a control mechanism 208 that controls the movement of components, such as the rotation of gantry 102 and the operation of x-ray source 104. In certain embodiments, control mechanism 208 further includes an x-ray controller 210 configured to provide power and timing signals to x-ray source 104. Control mechanism 208 further includes a gantry motor controller 212 configured to control the rotational speed and / or rotational position of gantry 102 based on imaging requirements.

[0022] In certain embodiments, the control mechanism 208 further includes a data acquisition system (DAS) 214 that samples analog data received from the detector elements 202 and converts the analog data to a digital signal for subsequent processing. The DAS 214 may be further configured to selectively aggregate data from a subset of the detector elements 202 into a so-called macro-detector. The data sampled and digitized by the DAS 214 is transmitted to a computer or computing device 216. In one example, the computing device 216 stores the data in a storage device or mass storage device 218. The storage device 218 may be, for example, any type of non-transitory memory and may include a hard disk drive, a floppy disk drive, a compact disk read / write (CD-R / W) drive, a digital versatile disk (DVD) drive, a flash drive, and / or a solid-state storage drive.

[0023] Additionally, the computing device 216 provides commands and parameters to one or more of the DAS 214, the X-ray controller 210, and the gantry motor controller 212 to control system operation (e.g., data acquisition and / or data processing). In certain embodiments, the computing device 216 controls system operation based on operator input. The computing device 216 receives operator input, including, for example, commands and / or scan parameters, through an operator console 220 operably coupled to the computing device 216. The operator console 220 may include a keyboard (not shown) or a touch screen to enable an operator to specify commands and / or scan parameters.

[0024] 2 shows one operator console 220, multiple operator consoles may be coupled to imaging system 200, for example, to input or output system parameters, request examinations, plot data, and / or display images. Additionally, in certain embodiments, imaging system 200 may be coupled to multiple displays, printers, workstations, and / or similar devices located locally, remotely, or at entirely different locations, e.g., within a facility or hospital, through one or more configurable wired and / or wireless networks (e.g., the Internet and / or virtual private networks, wireless telephone networks, wireless local area networks, wired local area networks, wireless wide area networks, wired wide area networks, etc.).

[0025] In one embodiment, for example, imaging system 200 includes or is coupled to a picture archiving and communication system (PACS) 224. In an exemplary implementation, PACS 224 is further coupled to remote systems (such as a radiology information system, a hospital information system, and / or an internal or external network (not shown)) to enable operators at different locations to provide commands and parameters and / or access image data.

[0026] The computing device 216 may use operator-supplied and / or system-defined commands and parameters to operate the table motor controller 226, which in turn may control the table 114. The table 114 may be a motorized table. Specifically, the table motor controller 226 may move the table 114 so that the subject 204 is properly positioned within the gantry 102 to acquire projection data corresponding to a target volume of the subject 204. In particular, the computing device 216 may be configured to control the movement of the table 114 in one or more directions. For example, in some examples, the computing device 216 may be configured to control the movement of the gantry 102 in the y- and z-directions, but not the x-direction, which correspond to the axis system 199 shown in FIG. 1 . In other embodiments, the computing device 216 may be configured to control the movement of the table 114 in all directions: the x-, y-, and z-directions. Additionally, the computing device 216 may be configured to control the tilt of the table 114, for example, by rotating the table about the z-axis and / or the x-axis.

[0027] As described above, DAS 214 samples and digitizes the projection data acquired by detector elements 202. Image reconstructor 230 then performs high-speed reconstruction using the sampled and digitized x-ray data. While image reconstructor 230 is shown as a separate entity in FIG. 2 , in certain embodiments, image reconstructor 230 may form part of computing device 216. Alternatively, image reconstructor 230 may not be present in imaging system 200, and computing device 216 may perform one or more functions of image reconstructor 230. Furthermore, image reconstructor 230 may be located locally or remotely and operably connected to imaging system 200 using a wired or wireless network. Notably, in one exemplary embodiment, the computing resources of a “cloud” network cluster may be used for image reconstructor 230.

[0028] In one embodiment, image reconstructor 230 stores the reconstructed image in storage device 218. Alternatively, image reconstructor 230 may transmit the reconstructed image to computing device 216 for generating patient information useful for diagnosis and evaluation. In certain embodiments, computing device 216 may transmit the reconstructed image and / or patient information to a display or presentation device 232 communicatively coupled to computing device 216 and / or image reconstructor 230. In some embodiments, the reconstructed image is transmitted from computing device 216 or image reconstructor 230 to storage device 218 for short-term or long-term storage.

[0029] Information can be transmitted between components present on the gantry 102 and external devices (e.g., computing device 216 and / or image reconstructor 230), thereby facilitating electronic communication with the rotating gantry. In some cases, the gantry and internal components (e.g., control mechanism 208, x-ray source 104, detector array 108) can be collectively defined as a PCCT scanner, in which case computing device 216 and image reconstructor 230 can reside external to the scanner.

[0030] Various methods and processes described further herein (such as those described below with reference to FIGS. 3-8) may be stored as executable instructions in a non-transitory memory of a computing device (or controller) of image processing system 200. In one embodiment, computing device 216 and / or image reconstructor 230 may include such executable instructions in non-transitory memory and may apply the methods described herein to reconstruct images and calculate distances for centering the phantom. In another embodiment, computing device 216 may include instructions in non-transitory memory and, after receiving a reconstructed image from image reconstructor 230, may apply, at least in part, the methods described herein to the reconstructed image. In yet another embodiment, the methods and processes described herein may be distributed between image reconstructor 230 and computing device 216.

[0031] In one embodiment, the display 232 allows the operator to evaluate the imaged anatomy. The display 232 also allows the operator to select a volume of interest (VOI) and / or request patient information, for example, through a graphical user interface (GUI), for performing subsequent scans or processing.

[0032] Although a PCCT system is described herein, it should be understood that other imaging systems (e.g., conventional CT systems, MRI systems, PET systems, single photon emission computed tomography (SPECT) systems, etc.) may be utilized without departing from the scope of the present disclosure.

[0033] 3, a flowchart of a general method 300 for automatically centering a phantom according to a first embodiment is shown. At least some aspects of method 300 may be performed according to instructions stored in a memory and executed by one or more processors of the imaging system (e.g., computing device 216 of imaging system 200). In some examples, one or more aspects of method 300 may be performed manually by a user. In some examples, method 300 may be performed in real time.

[0034] In step 302, method 300 includes identifying a phantom within the imaging system. As described above, the phantom can be placed by a user in an accessory slot or in an initial position on the imaging system table (e.g., placed in a designated holder). The phantom can be placed approximately at the isocenter of the imaging system. In some examples, a laser guide is provided to guide the user to the isocenter, and the user can manually use the gantry controls to roughly center the phantom. The phantom can be one of multiple identifiable phantoms known to the system. In some examples, the phantom can be identified by one or more parameters of a scout scan acquired with the phantom in its initial position. In other examples, the phantom can be identified based on user input. For example, the user can indicate the type of phantom to be used by selecting an option from a drop-down menu, by a search query, or the like. In further examples, the phantom can be identified by radio frequency identification (RFID) with an RFID tag or using a patient positioning camera.

[0035] In step 304, method 300 includes acquiring scan data of the phantom. The scan data of the phantom may, in some examples, be a scout scan or an axial scan with a lower resolution than a normal scan. In some examples, the scan data may be acquired after the computing device verifies that the height (e.g., position in the y-direction) of the system table is high enough for scanning. If the computing device does not verify that the height is high enough for scanning, the computing device may instruct a gantry control mechanism to move the table in the y-direction until it reaches a sufficient height. If the table height is changed, the initial position of the phantom may be updated based on the new height.

[0036] In step 306, method 300 includes calculating the distance to the isocenter in one or more directions. As further described with respect to FIGS. 4-7, the distance can be calculated in the x-, y-, and / or z-directions. In some cases, automatic movement in the x-direction may not be available. However, in such cases, the distance to the isocenter in the x-direction can still be determined. In particular, FIGS. 4-7 illustrate various embodiments for determining the distance to the isocenter. Specifically, FIGS. 4-6 illustrate a method for calculating the distance based on determining the position of edges in the lateral and vertical directions relative to the isocenter, and FIG. 7 illustrates a method for automatically centering a step / slab phantom in the lateral and rotational directions.

[0037] In step 308, method 300 includes adjusting the position of the phantom based on the calculated distances so that the phantom is aligned with the isocenter. As an example, the position of the phantom may be adjusted in the z direction based on a first calculated distance in the z direction, thereby adjusting the position of the table in the gantry in the z direction by the first calculated distance. In some embodiments, all table movements controlled by the gantry are automated and therefore may be performed automatically in response to determining the calculated distances (including all lateral movements (e.g., movements in the x direction), longitudinal movements (e.g., movements in the z direction), height changes (e.g., table movements in the y direction), and table tilts (e.g., table rotation about the z axis)). In other examples, table movements may be performed automatically for one or more distances rather than all calculated distances. For example, table movement in the x direction may not be automated, in which case automated movements are performed in other directions based on corresponding calculated distances, while a user may manually adjust the table position in the x direction based on the corresponding distances in the x direction determined in step 306.

[0038] Additionally, the calculated distances can be output to a display screen of the imaging system. In instances where automatic table movement in one or more directions is not available, the calculated distances in those directions can be displayed on the display screen for the user's reference as they manually adjust the table position.

[0039] In step 310, method 300 includes confirming the position of the phantom. In some examples, confirming the position of the phantom can include repeating the acquisition of scan data and repeating the calculation of the distance to the isocenter. If the calculated distance falls within a predefined threshold (e.g., less than 1 mm from the isocenter in all calculated directions), the position of the phantom is confirmed. If phantom misalignment still exists, the system can repeat the position adjustment as described above to align the phantom to the isocenter. In this manner, method 300 is repeated multiple times to accurately align the phantom, thereby avoiding misalignment errors in phantom imaging.

[0040] 4-6, a flowchart illustrating a method 400 for determining and correcting phantom misalignment is shown, according to a first embodiment of the present disclosure. At least some aspects of method 400 may be performed according to instructions stored in a memory and executed by one or more processors of the imaging system (e.g., computing device 216 of imaging system 200). In some examples, one or more aspects of method 400 may be performed manually by a user. In some examples, method 400 may be performed in real time.

[0041] In step 402, method 400 includes aligning a fiducial mark of the phantom to a laser guide of the imaging system. Placing the phantom on the table and aligning it based on the fiducial mark and the laser guide can be performed manually by an operator. For example, a phantom placed on the table (e.g., a phantom in direct surface contact with the table) can include a fiducial mark positioned at the center of the phantom or alternatively at the edge of the phantom. The fiducial mark can assist the user in initial alignment of the phantom, as the user can align the fiducial mark to the laser guide that corresponds to the position of the isocenter of the imaging system. The laser guide can indicate the isocenter in each of the x-, y-, and z-axes.

[0042] In step 404, method 400 includes receiving a scan acquisition request. The scan acquisition request can be received through a user input to an operator console of the imaging system (e.g., operator console 220 of imaging system 200). In some examples, the operator console can include a user input device (keyboard, touch screen, etc.), and a user can input the scan request via the user input device. In some embodiments, the phantom can be placed on a table (e.g., table 114) of the imaging system, for example, in direct surface contact with the table, in a designated holder, or in an accessory slot. Scan acquisition can be initiated based on specified parameters for scanning the phantom. For example, initiating the scan request can include identifying the type of phantom to be used.

[0043] At step 406, the method 400 includes acquiring scan data. As previously described, the scan acquisition may be performed according to a predefined protocol. The scan acquisition may include one or more image views. For example, one or more of an axial scan, a sagittal scout scan, and a coronal scout scan may be performed.

[0044] In step 408, method 400 includes determining whether the scan is valid. If the center row of the scan is sufficiently occluded by the object (e.g., a portion of the phantom), the scan can be determined to be valid. As described further below, the X and Y centering algorithms use the center row, so if the center row is not occluded by any portion of the phantom, performing the centering process will not produce usable output. Therefore, the center row is checked to see if it is sufficiently occluded. If it is valid (e.g., sufficiently occluded), method 400 proceeds to 410. If it is invalid (e.g., not sufficiently occluded), method 400 ends.

[0045] In step 410, method 400 includes extracting scan views at 180 degrees and 90 degrees. In some examples, scan acquisition includes acquiring one or more views, for example, an axial scan has multiple views depending on the rotation angle. For example, a sagittal view and a coronal view can be extracted from data acquired in an axial scan. The extracted 180-degree (coronal) view and the extracted 90-degree (sagittal) view can determine the distance to the isocenter in the y- and x-directions. In some embodiments, additional scan views can be extracted by an image reconstructor of the imaging system. In other embodiments, two scout scans at 180 degrees and 90 degrees can be used for the 180-degree and 90-degree views, respectively.

[0046] In step 412, method 400 determines whether the phantom completely blocks the imaging system's FOV in the x-direction. This means that the phantom covers all pixels of the detector and therefore uniformly attenuates x-rays, except for a slight angular dependence due to the fan x-ray beam. Therefore, a uniform image indicates that there are no x-ray irradiated areas due to misalignment. In instances where the phantom completely blocks the field of view, the phantom may be centered in the x- and y-directions. In instances where the phantom does not completely block the field of view (e.g., when non-phantom material is included in the scan acquisition FOV), the phantom may not be centered in one or both of the x- and y-directions. If the phantom completely blocks the field of view in the x-direction, method 400 proceeds to 414 (see FIG. 5). If the phantom does not completely block the field of view in the x-direction, method 400 proceeds to 420 (see FIG. 6).

[0047] In response to determining that the phantom completely obstructs the field of view in the x-direction, in step 414, method 400 includes locating the edge of the phantom in the z-direction, as shown in FIG. 5 . Locating the edge of the phantom in the z-direction can include analyzing X-ray scan data from a scout or axial scan to identify regions of the phantom that are homogeneous or uniform. A phantom of uniform thickness exhibits uniform X-ray attenuation in the scan image. In contrast, portions of the phantom with different thicknesses, portions of the table with different thicknesses, or portions of air without a phantom with different thicknesses exhibit significantly different X-ray attenuation. Therefore, the edge of the homogeneous region can be located by examining the image for a sudden drop or increase in X-ray attenuation. Because the width of the phantom is known, identifying regions of the phantom that are homogeneous or uniform can determine whether the phantom is isocentered with respect to the z-axis. If the phantom is not centered at the isocenter, the areas blocked by the phantom and the areas not blocked by the phantom in the z direction can be determined by searching for abrupt changes in x-ray attenuation in the scanned image. Based on the locations of the blocked and unblocked areas, the location of the edges of the phantom in the z direction can be detected.

[0048] In step 416, method 400 includes determining a first distance to the isocenter in the z-direction. The first distance can be a z-distance and can include both the magnitude and direction (e.g., negative or positive) of the movement. For example, a positive movement indicates that the table is moving further into the gantry, while a negative movement indicates that the table is moving further away from the gantry. The magnitude can be determined within a predefined threshold. For example, the distance can be calculated more precisely than can be achieved by the table movement. As a non-limiting example, the distance can be calculated to within tenths of a millimeter, but the table moves in millimeters even with the most precise movement. Thus, the output first distance can be output within the range of the table movement capabilities, e.g., in millimeters in the example provided.

[0049] In step 418, method 400 includes operating a table motor controller based on instructions from the computing device to move the phantom a first distance. As described with respect to FIG. 2, the table motor controller can be configured to adjust the position of the table relative to the gantry. Thus, the table motor controller can be operable to move the table a first distance in the z-direction. In some examples, the table movement may be performed in response to output of the first distance calculated in an automated manner without user input.

[0050] In response to determining that the phantom does not completely obstruct the field of view in the x-direction, method 400 continues to FIG. 6 and includes, at step 420, determining whether both edges of the phantom are present within the field of view. In some examples, the edge in the x-direction can be identified within a view extracted at 180 degrees. Determining whether an edge in the x-direction is present within the field of view can include analyzing x-ray scan data from the view extracted at 180 degrees to identify regions of the phantom that are homogeneous or uniform. A phantom of uniform thickness exhibits uniform x-ray attenuation in the scanned image. On the other hand, portions of the phantom with different thicknesses, portions of the table with different thicknesses, or portions of air without a phantom with different thicknesses will exhibit significantly different x-ray attenuation. Therefore, the edge of the homogeneous region can be located by examining the image for a sudden drop or increase in x-ray attenuation. If a sudden drop is detected, the edge is present within the field of view. If both edges of the phantom are within the field of view, the phantom may not be centered in the y-axis (e.g., the phantom is placed too close to the detector so that the phantom does not cover the entire detector) and may or may not be centered in the x-axis. If both edges of the phantom are not within the field of view, the phantom is centered in the y-direction but not in the x-direction. If both edges of the phantom are within the field of view, method 400 proceeds to step 424. If both edges of the phantom are not within the field of view, method 400 proceeds to step 422.

[0051] In step 422, method 400 includes determining a second distance in the x-direction. If both edges of the phantom in the x-direction are not within the field of view, for example, if one x-edge is within the field of view but the other x-edge is not, or if both x-edges are not within the field of view, the second distance in the x-direction can be calculated based on the length of the region exposed to the x-rays and the design margin of the phantom's x-width (known to the system). If both edges are not within the field of view, the phantom can be assumed to be aligned within the phantom's design margin. Following step 422, method 400 proceeds to step 430, described below.

[0052] In response to determining that both x-edges of the phantom are visible in the image, in step 424, method 400 includes determining whether the phantom is centered in the x-direction. As described above, if both x-edges are visible, the phantom may not be centered in the y-direction and may or may not be centered in the x-direction. Determining whether the phantom is centered in the x-direction may include locating the center of the phantom in the x-axis. Locating the center of the phantom in the x-axis may include locating the positions of the two x-edges by measuring the length of the region exposed to the x-rays. The point midway between the positions of the two x-edges may be the position of the center in the x-direction. If the center in the x-direction is aligned with the isocenter of the imaging system, the phantom is considered to be centered in the x-direction. If the center of the phantom in the x-direction is not aligned with the isocenter of the imaging system, the phantom may be considered not centered in the x-direction. If the phantom is centered, method 400 proceeds to step 428. If the phantom is not centered, method 400 proceeds to step 426.

[0053] In step 426, the method 400 includes determining a second distance in the x-direction. If the x-edge is visible in the image, determining the second distance in the x-direction can include determining a distance between the center of the phantom in the x-direction and the isocenter. The second distance can be the distance between the center of the phantom in the x-direction and the isocenter.

[0054] In step 428, method 400 includes determining a third distance in the y-direction. Determining the third distance in the y-direction can include locating the edge of the phantom in the y-direction in the scan image or in the 90-degree view. For example, the 180-degree extracted view can be used to determine the x-edge, and the 90-degree view can be used to determine the y-edge. As described above with respect to locating an edge in the z-direction and determining whether an edge exists in the x-direction, locating an edge in the y-direction can include analyzing the x-ray scan data from the extracted 90-degree view or analyzing the axial scan image to identify how homogeneous or uniform the phantom region is. A phantom of uniform thickness will appear in the scan image as uniform x-ray attenuation. However, portions of the phantom with different thicknesses, portions of the table with different thicknesses, or portions of air without the phantom with different thicknesses will have significantly different x-ray attenuation. Therefore, the edge of a homogeneous region can be located by examining a sudden decrease or increase in x-ray attenuation in the image. By identifying how homogeneous or uniform the phantom region is, the location of the edge can be identified in the y direction.

[0055] Once the position of the edge in the y direction is detected, the center in the y direction can be determined as described above with respect to determining the center in the y direction, and based on the position of the center in the y direction, a third distance to the isocenter in the y direction can be determined.

[0056] The first distance and the second distance can indicate a lateral displacement, including a displacement in the xz plane. The third distance can indicate a vertical displacement. In some examples, if one or more of the first distance, the second distance, and the third distance are zero, it indicates that the phantom is properly aligned in the corresponding direction. For example, for a step phantom, the table position in the y direction is predetermined, and therefore the calculated third distance in the y direction can be zero.

[0057] In some embodiments, the second distance and the third distance can be output to a computing device of the imaging system and an operator console of the imaging system. For example, the first distance, the second distance, and the third distance can be output to the computing device to perform automatic movement of the table. The second distance and the third distance can also be output to the operator console (e.g., to a display device of the operator console) for a user to review the calculated distances.

[0058] In step 430, method 400 includes operating a table motor controller to move a phantom (e.g., a phantom on a table) a second distance and / or a third distance. In some embodiments, the imaging system can include a table motor controller configured to move the table in the z and y directions but not in the x direction. In other embodiments, the imaging system can include a table motor controller configured to move the table in all directions: x, y, and z. A table motor controller such as that described with respect to FIG. 2 can be configured to adjust the position of the table relative to the gantry. Thus, the table motor controller can be operated to move the table a second distance in the x direction and / or a third distance in the y direction. If the phantom is centered in the y direction, the table motor controller can be operated to move the phantom a second distance (if automatic movement in the x direction is possible) but not in the y direction. If the phantom is not centered in the y direction, the table motor controller can be operated to move the phantom a second distance (if automatic movement in the x direction is possible) and a third distance. In this manner, the table can be moved in response to the output of the calculated distance in an automated manner without user input. If automatic movement in the x-direction is not available, the table can be moved a second distance manually by an operator.

[0059] In some examples, after centering the phantom in the x and y directions, method 400 can return to step 414 to determine the amount of centering movement required in the z direction, as described above. Thus, the phantom can be moved in the x, y, and z directions as needed based on the determination of the phantom's position in an automated manner.

[0060] In step 432, the method 400 includes repeating the scan acquisition. The scan acquisition can be performed with the phantom positioned at the new centered position. Verification of the adjusted center position can, in some instances, be performed using the same procedures described above for determining the amount of misalignment. Thus, performing repeated scan acquisitions with the phantom centered at the system isocenter can be used to calibrate the imaging system.

[0061] In this way, the phantom can be automatically centered from its initial position to be aligned with the isocenter of the imaging system. For example, a user can position the phantom on the table in any manner (e.g., on a designated mount), and the system can calculate the distance required to move the table to center the phantom and activate the table motor controller to align the phantom to the isocenter. This reduces the human error of phantom misalignment that can occur with manual laser-guided alignment, thereby improving the accuracy of the calibration scan. Furthermore, the need for manual repositioning and repeated data acquisition as a result of phantom misalignment is reduced, saving time and user effort.

[0062] Referring now to FIG. 7 , a flowchart illustrating a method 700 for determining and correcting phantom misalignment according to a second embodiment of the present disclosure is shown. At least some aspects of the method 700 may be performed according to instructions stored in a memory and executed by one or more processors of an imaging system, such as the computing device 216 of the imaging system 200 described with respect to FIG. 2 above. In some examples, one or more aspects of the method 700 may be performed manually by a user. In some examples, the method 700 may be performed in real time during the collection of calibration data. In some examples, the second embodiment method 700 may be applied to layered slab phantoms, step phantoms, etc., that include multiple distinct regions.

[0063] In step 702, method 700 includes receiving a request to initiate a scan of a phantom placed on a table. In some examples, the phantom placed on the table (e.g., a phantom in direct surface contact with the table) can include a fiducial mark. The fiducial mark may be placed at the center of the phantom or, alternatively, at the edge of the phantom. The fiducial mark can assist a user in initially aligning the phantom, as the user can align the fiducial mark with a laser guide corresponding to the location of the isocenter of the imaging system. The laser guide can indicate the isocenter in each of the x-, y-, and z-axes. In some examples, the table height, and therefore the phantom's position in the y-direction, is predetermined for a particular slab or step phantom, in which case the fiducial mark can be aligned by the user with the laser guide in the z- and x-directions, and the phantom can be placed at the predetermined table height in the y-direction.

[0064] In step 704, method 700 includes acquiring scan data for a current stage of the phantom. In some examples, each stage or layer of multiple stages or layers of the phantom can be scanned separately in sequence. In some examples, the first step in the series of steps can be the first step in the z-direction. As described herein, determining misalignment can be performed iteratively for each scanned step. In a first iteration of the method, the current stage can be the first stage in the scanning sequence. In subsequent iterations, the current stage can be a subsequent stage of the phantom.

[0065] In step 706, method 700 includes applying an edge detection algorithm to determine whether the edge of the current phantom stage is outside the field of view. If the phantom is properly aligned, all edges of the current phantom stage are considered to be within the field of view of the imaging system, and therefore the current phantom stage can cover all detector pixels and attenuate x-rays. If any detector pixels through which x-rays are emitted detect unattenuated x-rays, the phantom may be misaligned. Furthermore, if a portion of the detector covers the next phantom stage, the phantom may be misaligned. As described with respect to method 400, the edge detection algorithm may include analyzing x-ray scan data to identify how homogeneous or uniform phantom regions are. A phantom of uniform thickness will exhibit uniform x-ray attenuation in the scanned image. In contrast, portions of a phantom with different thicknesses, portions of a table with different thicknesses, or portions of air without a phantom with different thicknesses will exhibit significantly different x-ray attenuation. Therefore, the edges of homogeneous regions can be located by examining the image for abrupt drops or increases in x-ray attenuation. By determining how homogeneous or uniform the phantom region is, the location of the edges can be defined and therefore whether the edges are in or out of the field of view.

[0066] In step 708, method 700 includes determining whether all edges are within the field of view based on the edge detection algorithm applied in step 706. As described above, if an edge is present within the field of view, it may be laterally offset. If an edge is not within the field of view, the phantom may be laterally centered. If the edge detection algorithm detects that an edge is outside the field of view (NO in step 708), method 700 proceeds to step 712. If the edge detection algorithm detects that an edge is within the field of view (YES in step 708), method 700 proceeds to step 710.

[0067] In step 710, method 700 includes determining a lateral shift. The lateral shift can represent the phantom shift in the xz plane. For example, the left-right shift (e.g., shift in the x-direction) and the shift during loading and unloading from the gantry (e.g., shift in the z-direction) can be determined. The lateral shift can be determined based on an edge detection algorithm. As an example, the distance between the position of the detected edge of the phantom and the position of the edge of the detector pixel illuminated by the x-rays can be used to determine the lateral shift. As another example, the edge detection algorithm can include determining the position of the center of the phantom, which can be compared to the position of the isocenter to determine the lateral shift. Thus, the lateral shift can indicate the distance for alignment in one or more directions.

[0068] In step 712, method 700 includes determining whether the phantom is level on the table. Determining whether the phantom is level can include determining an average count value of the leftmost pixel and the rightmost pixel. If the count value of the leftmost pixel is greater than the count value of the rightmost pixel, the phantom can be determined to be tilted to the left. Similarly, if the count value of the rightmost pixel is greater than the count value of the leftmost pixel, the phantom can be determined to be tilted to the right. If the phantom is level on the table (YES in step 712), method 700 proceeds to step 716. If the phantom is not level on the table (NO in step 712), method 700 proceeds to step 714.

[0069] In step 714, method 700 includes determining a tilt offset. As described in step 712, a tilt offset can be detected when the pixel count value of the leftmost pixel and the pixel count value of the rightmost pixel are not equal. Thus, the difference in pixel count values ​​can indicate a tilt offset, with a larger offset corresponding to a larger tilt. Therefore, a tilt amount for alignment (e.g., a rotation amount for leveling) can be generated from the tilt offset.

[0070] In step 716, method 700 includes adjusting the table position to align the phantom. The table position can be adjusted based on the tilt offset (e.g., the determined rotation amount for leveling determined in step 714) and the lateral offset (e.g., the lateral distance for alignment determined in step 710). As described with respect to method 400, adjusting the table position can be fully automated, partially automated, or, in some instances, fully manual. For example, a table motor controller can automatically control table movement in all x, y, and z directions, including automatic rotation about one or more of multiple axes (e.g., rotation about the z axis), in response to determining the lateral and tilt offsets. As previously described, the phantom position in the y direction (and therefore the table position) can be predetermined for the particular slab or step phantom being used. In such an example, the determined tilt amount for alignment and the determined lateral distance for alignment can be output to a computing device, which can then instruct a table motor controller to adjust the position of the table based on the tilt amount and distance.

[0071] In some examples, adjusting the table position may not include movement in the y-direction if the table height is already at a predetermined position. In other examples, adjusting the table position may include moving the table in the y-direction to reach a predetermined position. Furthermore, in some examples, automatic movement in one or more of a plurality of directions (e.g., the x-direction) may not be available. In such examples, automatic movement may be available in other directions, while manual movement in the one or more directions not available for automatic movement may be performed by a user. In such examples, the amount of automatic movement may be output to a computing device as described above, and the amount of manual movement may be output to an operator console for viewing by a user. In yet other examples, automatic movement in all directions may not be available, in which case a user may manually perform movement via a table motor controller and / or a gantry controller. In such examples, the amount of movement may be output to an operator console, allowing a user to view and act on the amount of movement.

[0072] In step 718, method 700 determines whether there is a next stage of the phantom. As previously described, a step phantom or a slab phantom can have multiple stages or layers, respectively. Each stage or layer can be imaged by multiple successive data acquisitions (or each stage or layer corresponds to a successive data acquisition portion of a single data acquisition). If a subsequent stage of the phantom is to be imaged (YES in step 718), method 700 returns to step 704, moves the table by the designed step width in the z direction, and then acquires scan data for the current stage of the phantom. The subsequent stage of the phantom thus becomes the current stage, and method 700 proceeds as described above. In this manner, method 700 can be performed repeatedly for each stage of the phantom to ensure proper alignment of the phantom at each stage.

[0073] Therefore, by properly aligning the phantom (including properly aligning each step or layer of the phantom, if the phantom is a step or slab phantom), accurate calibration of the imaging system can be ensured. As described above, the phantom contains imageable materials of different densities that exhibit known, reproducible x-ray attenuation maps so that the imaging system can be calibrated. Misalignment of the phantom will produce inaccurate results, and therefore calibrations based on inaccurate results are likely to be inaccurate. The method described above checks for and corrects for misalignment, thereby improving the accuracy of imaging system calibrations and reducing the need for repeated calibrations.

[0074] 8 to 10, various examples of phantom misalignment are shown. For example, Figures 8 and 9 show phantom misalignment in particular in the lateral direction, and Figure 10 shows tilt misalignment in particular.

[0075] 8, a first example of phantom misalignment 800 is shown. In the first example of phantom misalignment 800, the phantom 806 is a step phantom. For example, a detector 802 of an imaging system is positioned opposite an X-ray focal point 804. X-rays emanate from the X-ray focal point 804 toward the detector 802 and pass through the phantom 806. The phantom 806 may include multiple steps (e.g., a first step 812 and a second step 814 positioned adjacent to each other along the z-axis). The phantom 806 may be positioned on the end of the table 808 by mounting holes located at the end of the table 808.

[0076] The radiation beam 820 can define a volume within which x-rays are emitted from the x-ray focal point 804 towards the detector 802. The phantom 806 intersects with the radiation beam 820. The table 808 and the position of the phantom 806 on the table 808 can affect where the intersection is and therefore whether part of the phantom is outside the field of view. For example, the phantom 806 can be positioned such that the first stage 812 is within the radiation beam 820. In the first example 800 of phantom misalignment, the phantom 806 is misaligned laterally with respect to the z-axis, such that part of the first stage 812 is outside the radiation beam 820 and part of the second stage 814 is inside the radiation beam 820.

[0077] As described above, the edges of the phantom can be identified, particularly the edge of the first step 812 of the phantom in the example of the step phantom. For example, a first edge 816 and a second edge 818 can be identified. The first edge 816 and the second edge 818 can be z-axis edges. When the position of the first edge 816 is identified, it can be shown that the first edge 816 is within the radiation beam 820, and the second edge 818 is outside the radiation beam 820, separated from the first edge 816 by a distance equal to the designed width of the step phantom. Furthermore, the first edge 816 is also the edge of the second step 814, and an overlap portion 810 (the portion where the second step 814 is within the radiation beam 820) can occur in the radiation beam 820.

[0078] Thus, the positions of the first edge 816 and the second edge 818 relative to the position of the radiation beam 820 can determine the movement of the table in the x-direction to align the phantom (e.g., the first stage 812). Thus, Figure 8 illustrates a first type of misalignment relative to the z-axis, whereby the phantom is positioned too far inside the gantry of the imaging system, and therefore the movement to align the phantom, determined based on the position of the phantom, can include moving the position out of the gantry along the z-axis.

[0079] While a step phantom is shown herein, it should be understood that other types of phantoms can be used without departing from the scope of this disclosure. Furthermore, it should be understood that edges can be identified in other directions not shown in Figure 8, and that centers can be found instead of edges in some axes. For example, edges can be identified in the z-direction of a non-step or slab phantom, as described with respect to Figures 4-6, or centers can be found in the x-direction, as described with respect to Figure 7.

[0080] 9, a second example of phantom misalignment 900 is shown. In the second example of phantom misalignment 900, the phantom 906 is a step phantom. For example, a detector 902 of an imaging system can be positioned opposite an X-ray focal point 904. X-rays radiate from the X-ray focal point 904 toward the detector 902 and pass through the phantom 906. The phantom 906 can include multiple steps (e.g., a first step 912). The phantom 906 can be positioned in surface contact with a table 908.

[0081] The radiation beam 920 can define a volume within which x-rays are emitted from the x-ray focal point 904 towards the detector 902. The phantom 906 intersects with the radiation beam 920. The position of the table 908 and the phantom 906 on the table 908 can affect where the intersection is and therefore whether part of the phantom is outside the field of view. For example, the phantom 906 can be positioned such that the first stage 912 is partially within the radiation beam 920, as shown. In the second example 900 of phantom misalignment, a lateral misalignment of the phantom 906 relative to the z-axis causes part of the first stage 912 to be outside the radiation beam 920.

[0082] As described above, the edges of the phantom can be identified, particularly the edge of the first step 912 of the phantom in the example of the step phantom. At the location of the first step 912, where the second edge 918 is within the radiation beam 920 and the first edge 916 is outside the radiation beam 920, a portion 910 of the radiation beam 920 will be unattenuated x-rays. The attenuation difference due to the partial exposure can be used to first identify the second edge 918. Even though the first edge 916 is outside the beam 920, the position of the first edge 916 can be estimated from the position of the second edge 918 in the detector signal because the phantom step has a known width from engineering design.

[0083] Thus, the positions of the first edge 916 and the second edge 918 relative to the position of the radiation beam 920 can determine the movement of the table in the x-direction to align the phantom (e.g., the first stage 812). Figure 9 therefore shows a second type of misalignment with respect to the z-axis, where the phantom is positioned so that it is not too far into the gantry of the imaging system, and therefore the movement to align the phantom, determined based on the position of the phantom, can include moving the position of the phantom further into the gantry along the z-axis.

[0084] 10, a third example of phantom misalignment 1000 is shown. A detector 1002 of an imaging system is positioned opposite an X-ray focal spot 1004. X-rays are emitted from the X-ray focal spot 1004 towards the detector 1002 and pass through a phantom 1006.

[0085] The radiation beam 1020 can define a volume within which x-rays are emitted from the x-ray focal point 1004 toward the detector 1002. The phantom 1006 intersects with the radiation beam 1020. Tilting the phantom 1006 with respect to the z-axis can result in a pixel count value for the leftmost pixel being different from a pixel count value for the rightmost pixel. For example, a first portion 1008 of the phantom 1006 corresponds to the leftmost pixel in an acquired image of the phantom 1006, and a second portion 1010 of the phantom 1006 corresponds to the rightmost pixel in the acquired image. The first portion 1008 intersects at a first angle resulting in a first pixel count value, and the second portion 1010 intersects at a second angle resulting in a second pixel count value. In some examples, the second pixel count value can be less than the first pixel count value due to a difference in x-ray path length between the first portion 1008 and the second portion 1010. The difference between the first pixel count value and the second pixel count value can indicate how tilted the phantom 1006 is, based on known parameters of the radiation beam 1020 .

[0086] According to the Beer-Lambert law, the path length between the first portion 1008 and the second portion 1010 is I=I0exp (μ*x) where I is the incident x-ray flux count, I is the measured count, μ is the attenuation coefficient, which is primarily dependent on the material of the step phantom and the x-ray energy, and x is the path length. Once the path lengths of the first portion 1008 and the second portion 1010 are calculated, the tilt angle can be estimated. Thus, the first pixel count value, the second pixel count value, and the difference between the pixel count values ​​can determine the amount of tilt of the phantom or the amount of rotation of the phantom about the z-axis. For example, in the third example phantom misalignment 1000 shown in FIG. 10 , tilting for centering can include rotating the phantom clockwise about the z-axis to lower the second portion 1010 and / or raise the first portion 1008, thus leveling the phantom 1006.

[0087] 11 is a flowchart illustrating a method 1100 for determining displacement in the x and y directions according to a third embodiment of the present disclosure. At least some aspects of the method 1100 may be performed according to instructions stored in a memory and executed by one or more processors of the imaging system (such as the computing device 216 of the imaging system 200 described with reference to FIG. 2 above). In some examples, one or more aspects of the method 1100 may be performed manually by a user. In some examples, the method 1100 may be performed in real time during the collection of calibration data. In some examples, the method 1100 of the second embodiment may be applied to a layered slab phantom, a step phantom, or the like, including multiple distinct regions, although it should be understood that the method may be applied to any type of phantom.

[0088] In step 1102, method 1100 includes identifying a phantom placed in the imaging system. In some examples, a scan initiation request based on user input to an imaging system operator console can include identifying the type of phantom to be imaged. For example, in some examples, a user can enter a search query or the like by selecting from a drop-down menu. In another example, the phantom can be identified using RFID recognition or a patient positioning camera of the imaging system. In the case of a step phantom, the phantom placed by the user can be electronically matched between the user input and an RFID attached to the phantom to confirm that the matched phantom is placed on the gantry. In another example, a user can select a specific calibration scan protocol that corresponds to the phantom to be imaged and thereby identifies the phantom. The slab or step phantoms discussed herein can be placed in the bore of the imaging system.

[0089] In step 1104, the method 1100 includes acquiring an axial scan of the phantom. As mentioned above, the scan acquisition can be performed according to a predefined protocol.

[0090] In step 1106, the method 1100 includes reconstructing a sinogram of a single row of a detector of the imaging system. The sinogram may be a 2D image showing the raw data of the axial scan (e.g., the raw data before an image reconstruction algorithm is applied by an image reconstructor). For example, the projection data acquired during the collection of the axial scan may be organized into a 2D array with one axis representing the angle of projection and the other axis representing the position along the detector. For example, the sinogram may be represented by views on the X-axis and channels on the Y-axis.

[0091] In step 1108, method 1100 includes designating three or more points on the phantom. These points can be any pixel or group of pixels on the imaged phantom. For example, each of these points can be an edge of the phantom, coincident with a fiducial marker on the phantom, the center of the phantom, or another point on the phantom. In some examples, each of these points can be designated on a different edge of the phantom, and each point can be adjacent to air and not obscured by the remainder of the phantom's body, although it should be understood that these points can be any point on the phantom. In some examples, the phantom is a 3D object, and therefore, at least three points can be designated to determine the orientation and position of the phantom.

[0092] In step 1110, method 1100 includes tracking a specified point across different angular views of an axial scan. In some examples, the axial scan can be transformed into sinogram space. The specified point is not within the field of view in some views but is within the field of view in other views, thus moving in and out of sinogram space.

[0093] Referring to FIG. 12A , an exemplary diagram of different angular views of an axial scan of a phantom is shown. For example, a phantom 1212 can be positioned between an X-ray source 1210 and a detector 1208 in an imaging system. A radiation beam 1216 emanates from the X-ray source 1210, passes through the phantom 1212, is attenuated, and reaches the detector 1208. A first point 1214 and a second point 1218 of the phantom 1212 can be designated as described herein. The first point 1214 and the second point 1218 are in the same plane of the phantom. As previously mentioned, more than two points can be designated. Thus, a third point of the phantom 1212, not shown in either FIG. 12A or FIG. 12B , can be designated in a different plane of the phantom.

[0094] In the first angle view 1202, the first point 1214 and the second point 1218 are located outside the radiation beam 1216 and therefore outside the field of view of the imaging system. When a point is located outside the field of view, it is located outside of sinogram space. In the second angle view 1204, the first point 1214 and the second point 1218 are both at a position that intersects with the beam of radiation 1216 and therefore are within the field of view of the imaging system. In the third angle view 1206, the first point 1214 is at a position that intersects with the radiation beam 1216, but the second point 1218 is outside the field of view of the imaging system. Thus, the first point 1214 is within the field of view of the imaging system and therefore within sinogram space, but the second point 1218 is not in sinogram space. As described below, any two angular view data (such as first angular view 1204 and second angular view 1206) can be used to calculate the precise locations of specified points 1214 and 1218.

[0095] Returning to FIG. 11 , in step 1112, method 1100 includes determining the distance between the specified point and the geometric isocenter channel for each of the different angle views. In some examples, the distance between the specified point and the isocenter channel is determined for angles when the point is within sinogram space, and not for angles when the point is outside sinogram space. Because the x-ray tube and detector are fixed to the gantry and therefore rotate together around the gantry geometric isocenter without changing the relative positions of the x-ray tube and detector, the isocenter channel 1220 is naturally defined as the gantry geometric center channel. The distance between the specified point and the isocenter channel can be represented by a perpendicular line as the shortest distance between the specified point and the isocenter channel.

[0096] Referring to Figure 12B, an exemplary diagram of Figure 12A is shown. As described above, because the scanner gantry rotates around a fixed geometric center point, the isocenter channel 1220 of the imaging system can be naturally defined. In some examples, as described above, when a specified point is located in sinogram space, such as in the second and third angle views 1204 and 1206, the distance between the point and the isocenter channel 1220 can be determined. For example, when the phantom is located at the second angle view 1202, a first distance 1224 between the first point 1214 and the isocenter channel 1220 can be determined, and a second distance 128 between the second point 1218 and the isocenter channel 1220 can be determined. When the phantom is positioned at the third angle view 1208, a third distance 1226 between the first point 1214 and the isocenter channel can be determined, but the distance between the second point 1218 and the isocenter channel 1220 cannot be determined because the second point 1218 is out of sinogram space in the third angle view 1208. Similarly, if both the first point 1214 and the second point 1218 are out of sinogram space in the first angle view 1202, no distance can be determined.

[0097] In step 1114, method 1100 includes determining the position of the designated point in the x-y plane of the system. Since the distance between one of the three or more designated points and the isocenter channel is known for any two or more views, the angle of the gantry provides the angle of the scan view, thereby allowing the distance at that angle of the gantry to be determined. Therefore, the position of the designated point can be determined based on the determined distance from the isocenter channel at that angle of the gantry. In summary, the x-y coordinates of each designated point can be calculated using the two angles and two distances.

[0098] In step 1116, method 1100 includes determining a position of the phantom relative to the isocenter of the imaging system based on the positions of the specified points. Thus, the position of the phantom relative to the isocenter can indicate distances to move in the x and y directions so that the phantom is centered. As explained above, outputting these determined distances can indicate automatic movements to be made by a table motor controller to center the phantom relative to the isocenter of the imaging system. As mentioned above, method 1100 may be directed to determining misalignments in the x and y directions, but does not determine misalignments in the z direction. Determining the misalignment in the z direction may be performed as described above in the first or second embodiment.

[0099] In some examples, method 1100 can be performed once for a first specified point to determine the lateral / vertical position of the phantom, which can then be translationally centered by linear movement in the x and y directions if the phantom is horizontal. Method 1100 can be performed a second time for a second specified point to determine phantom tilt or phantom misalignment, which can then be rotationally centered automatically by rotating about the x or y axis. In other examples, three or more specified points can allow for simultaneous adjustment of both translation and tilt.

[0100] A technical effect of the systems and methods provided herein is the ability to automatically center a phantom during the calibration process. By identifying and correcting phantom misalignment, the phantom can be fully and properly imaged to ensure accuracy. By properly imaging the phantom, calibration can be performed more accurately. During calibration, misalignment can be corrected by calculating the distance to the center and automatically centering the phantom. In this way, misalignment errors due to human error can be reduced. Furthermore, the time spent repeating imaging and manually realigning the phantom can be reduced. Furthermore, automatically centering the phantom reduces the need for repeat scans due to misalignment, thereby reducing the processing load for the system's calibration scans.

[0101] The present disclosure also supports a method for an imaging system. The method includes acquiring scan data of a phantom, determining one or more distances from the phantom to a center of the imaging system, and automatically adjusting a position of the phantom based on the one or more distances to the center. In a first embodiment of the method, determining the one or more distances to the center includes detecting an edge of the phantom, determining a first distance to the center in a z-direction among the one or more distances to the center, and determining a second distance to the center in an x-direction and a third distance to the center in a y-direction among the one or more distances to the center. In a second embodiment of the method, which optionally includes the first embodiment, automatically adjusting the position of the phantom based on the one or more distances to the center includes adjusting a table of the imaging system by the first distance to the center in the z-direction, by the second distance to the center in the x-direction, and by the third distance to the center in the y-direction. In a third embodiment of the method, optionally including one or both of the first and second embodiments, automatically adjusting the position of the phantom based on the one or more distances to the center includes adjusting a table of the imaging system by the first distance to the center in the z-direction and by the third distance to the center in the y-direction. In a fourth embodiment of the method, optionally including one or more of the first through third embodiments, if the phantom is a step phantom, determining the one or more distances to the center includes applying an edge detection algorithm to the scan data for each step of the step phantom, determining lateral shifts of the step phantom in the x- and y-directions, and determining a tilt shift of the step phantom. In a fifth embodiment of the method, optionally including one or more of the first through fourth embodiments, determining the tilt shift includes determining a difference between a first pixel count value of a leftmost pixel and a second pixel count value of a rightmost pixel.In a sixth embodiment of the method, optionally including one or more of the or each of the first to fifth embodiments, further comprising outputting the one or more distances to the center to an operator console. In a seventh embodiment of the method, optionally including one or more of the or each of the first to sixth embodiments, the imaging system is one of a photon counting computed tomography (PCCT) system and a computed tomography (CT) system.

[0102] The present disclosure also supports a system. The system includes a computing device communicatively coupled to an imaging system configured to image a phantom, the computing device configured to use instructions stored in a non-transitory memory that, when executed, cause the computing device to identify a phantom to be imaged, acquire scan data of the phantom, determine a displacement of the phantom in one or more directions, and automatically adjust a position of the phantom based on the displacement. In a first embodiment of the system, identifying the phantom includes one or more of receiving user input selecting the phantom from a menu of phantom options and verifying a radio frequency identification tag (RFID). In a second embodiment of the system, which optionally includes the first embodiment, the computing device is configured to use instructions stored in a non-transitory memory to determine the displacement of the phantom, the instructions, when executed, cause the computing device to apply an edge detection algorithm to determine a position of an edge of the phantom in a z-direction. In a third embodiment of the system, which optionally includes one or both of the first and second embodiments, the scan data is an axial scan of the phantom, and the computing device is configured to use instructions that, when executed, cause the computing device to extract 180-degree and 90-degree scan views. In a fourth embodiment of the system, which optionally includes one or more of the first through third embodiments, to determine the displacement of the phantom, the computing device is configured to use instructions stored in non-transitory memory that, when executed, cause the computing device to detect and extract the phantom from each of the 180-degree and 90-degree scan views, determine a location of a center of the phantom in an x-direction and a location of the center of the phantom in a y-direction, and compare the location of the center of the phantom to an isocenter of the imaging system.In a fifth embodiment of the system, which optionally includes one or more of the first to fourth embodiments, the computing device is configured to use instructions stored in a non-transitory memory to determine the amount of displacement of the phantom, the instructions, when executed, causing the computing device to determine a first pixel count value of a leftmost pixel of the scan data, a second pixel count value of a rightmost pixel of the scan data, and a difference between the first and second pixel count values ​​to determine a slope displacement amount of the amount of displacement. In a sixth embodiment of the system, which optionally includes one or more of the first to fifth embodiments, the computing device is configured to automatically adjust the position of the phantom by adjusting the position of a table on which the phantom is placed in a z-direction and a y-direction with a table motor controller. In a seventh embodiment of the system, optionally including one or more of the first to sixth embodiments, the computing device is further configured to automatically adjust the position of the table in an X direction by the table motor controller.In an eighth embodiment of the system, which optionally includes one or more or each of the first to seventh embodiments, to determine the amount of shift of the phantom, the computing device is configured to use instructions in a non-transitory memory, which, when executed, cause the computing device to: reconstruct a sinogram of a row of detectors of the imaging system; track three or more designated points of the phantom at different angular views of an axial scan; determine, for each of the different angular views, a distance between each of the three or more designated points and an isocenter channel of the imaging system; determine a position of each of the three or more designated points based on the distance between each of the three or more designated points and the isocenter channel and an angle of a gantry of the imaging system; and determine a position of the phantom relative to the isocenter of the imaging system based on the positions of the three or more designated points.

[0103] The present disclosure also supports a method for automatically centering a phantom, the method including acquiring scan data of the phantom on a table with an imaging system, determining a first distance in the z-direction from the center of the phantom to an isocenter of the imaging system, determining a second distance in the y-direction from the center of the phantom to the isocenter, determining a third distance in the x-direction from the center of the phantom to the isocenter, and moving the table the first, second, and third distances to align the center of the phantom with the isocenter of the imaging system. A first embodiment of the method further includes determining a rotation amount to level about the z-axis and rotating the table so that the table is level. In a second embodiment of the method, which optionally includes the first embodiment, determining the first distance includes applying an edge detection algorithm to determine whether the phantom is present in a field of view.

[0104] As used herein, elements or steps described in the singular and preceded by the words "a" or "an" should be understood not to exclude a plurality of such elements or steps, unless the exclusion of a plurality of such elements or steps is expressly stated. Furthermore, references to "one embodiment" of the invention are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features. Furthermore, unless expressly stated to the contrary, embodiments "comprising," "including," or "having" an element or elements having a particular characteristic may include additional such elements that do not have that characteristic. The terms "including" and "in which" are used as shorthand for the terms "comprising" and "wherein," respectively. Terms such as "first," "second," and "third" are used merely as labels, and are not intended to impose numerical requirements or a specific positional order on the objects of these terms.

[0105] This specification uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the relevant art to practice the invention (e.g., to make and use the devices or systems, and to perform the incorporated methods). The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements that do not differ insubstantially from the literal language of the claims. [Explanation of symbols]

[0106] 100 PCCT System

Claims

1. 1. A method for an imaging system, comprising: acquiring scan data of the phantom; determining one or more distances from the phantom to a center of the imaging system; and automatically adjusting the position of the phantom based on one or more distances to the center. A method comprising:

2. Determining the one or more distances to the center may include: detecting edges of the phantom; determining a first distance to the center in the z-direction among the one or more distances to the center; and determining a second distance to the center in an x-direction and a third distance to the center in a y-direction of the one or more distances to the center; The method of claim 1 , comprising:

3. 3. The method of claim 2, wherein automatically adjusting the position of the phantom based on the one or more distances to the center comprises adjusting a table of the imaging system by the first distance to the center in a z-direction, by the second distance to the center in an x-direction, and by the third distance to the center in a y-direction.

4. 3. The method of claim 2, wherein automatically adjusting the position of the phantom based on the one or more distances to the center comprises adjusting a table of the imaging system by the first distance to the center in a z-direction and by the third distance to the center in a y-direction.

5. If the phantom is a step phantom, determining the one or more distances to the center may include, for each step of the step phantom: applying an edge detection algorithm to the scan data; determining lateral displacements of the step phantom in the x and y directions; and determining the amount of tilt deviation of the step phantom; The method of claim 1 , comprising:

6. The method of claim 5 , wherein determining the amount of tilt deviation comprises determining a difference between a first pixel count value of a leftmost pixel and a second pixel count value of a rightmost pixel.

7. The method of claim 1 , further comprising outputting the one or more distances to the center to an operator console.

8. The method of claim 1 , wherein the imaging system is one of a photon counting computed tomography (PCCT) system and a computed tomography (CT) system.

9. 1. A computing device communicatively coupled to an imaging system configured to image a phantom, the computing device configured to use instructions in a non-transitory memory, the instructions, when executed, causing the computing device to: identifying a phantom to be imaged; acquiring scan data of the phantom; determining the displacement of the phantom in one or more directions; and automatically adjusting the position of the phantom based on the amount of deviation. A system that executes the following.

10. 10. The system of claim 9, wherein identifying the phantom includes one or more of receiving user input selecting the phantom from a menu of phantom options and verifying a radio frequency identification tag (RFID).

11. 10. The system of claim 9, wherein to determine the amount of displacement of the phantom, the computing device is configured to use instructions stored in a non-transitory memory, the instructions, when executed, causing the computing device to apply an edge detection algorithm to determine the position of an edge of the phantom in a z-direction.

12. 10. The system of claim 9, wherein the scan data is an axial scan of the phantom, and the computing device is configured to use instructions that, when executed, cause the computing device to extract 180 degree and 90 degree scan views.

13. To determine the displacement of the phantom, the computing device is configured to use instructions stored in a non-transitory memory, the instructions, when executed, causing the computing device to: Detecting and extracting the phantom from each scan view at 180 degrees and 90 degrees; determining the position of the center of the phantom in the x-direction and the position of the center of the phantom in the y-direction; and Comparing the location of the center of the phantom with the isocenter of the imaging system. The system of claim 12 , wherein the system executes the following:

14. To determine the displacement of the phantom, the computing device is configured to use instructions stored in a non-transitory memory, the instructions, when executed, causing the computing device to: determining a first pixel count value of a leftmost pixel of the scan data; determining a second pixel count value of a rightmost pixel of the scan data; and determining a difference between the first pixel count value and the second pixel count value to determine a slope deviation amount of the deviation amount; The system of claim 9 , wherein the system executes the following:

15. 10. The system of claim 9, wherein the computing device is configured to automatically adjust the position of the phantom by adjusting the position of a table on which the phantom is placed in the z and y directions using a table motor controller.

16. 16. The system of claim 15, wherein the computing device is further configured to automatically adjust the position of the table in an X direction with the table motor controller.

17. To determine the displacement of the phantom, the computing device is configured to use instructions in a non-transitory memory, the instructions, when executed, causing the computing device to: reconstructing a sinogram of a row of detectors of said imaging system; tracking three or more designated points of the phantom in different angular views of an axial scan; determining, for each of the different angular views, a distance between each of the three or more designated points and an isocenter channel of the imaging system; determining a position of each of the three or more designated points based on a distance between each of the three or more designated points and the isocenter channel and an angle of a gantry of the imaging system; and determining a position of the phantom relative to an isocenter of the imaging system based on the positions of the three or more specified points; The system of claim 9 , wherein the system executes the following:

18. 1. A method for automatically centering a phantom, comprising: acquiring scan data of the phantom on a table with an imaging system; determining a first distance in a z-direction from a center of the phantom to an isocenter of the imaging system; determining a second distance in a y direction from the center of the phantom to the isocenter; determining a third distance in an x-direction from the center of the phantom to the isocenter; and moving the table the first distance, the second distance, and the third distance to align the center of the phantom with the isocenter of the imaging system; A method comprising:

19. 20. The method of claim 18, further comprising determining an amount of rotation to level about the z-axis and rotating the table so that the table is level.

20. 20. The method of claim 18, wherein determining the first distance comprises applying an edge detection algorithm to determine whether the phantom is present within a field of view.

Images