System and method for motion guided retrospective gating

Abstract

The invention relates to a system and method for motion guided retrospective gating. An imaging system and a method of using the imaging system are described. In one example, a method of identifying movement of a patient during a medical imaging scan, the method comprising: initiating a motion detection data acquisition; initiating a medical imaging scan of the patient to acquire scan data; determining a motion score curve for a duration of the medical imaging scan based on the motion detection data; removing a portion of the scan data corresponding to a motion score curve outside an acceptable range; and selecting scan data corresponding to the motion score curve within the acceptable range for reconstruction.

Description

Background Art

[0001] The subject matter disclosed herein relates to medical imaging systems, and more particularly to detecting motion during a computed tomography (CT) scan using one or more sensors or systems to detect motion. These sensors may include cameras incorporated within a CT imaging system and / or laser imaging, detection and ranging (LiDAR) based technologies.

[0002] In CT, X-ray radiation is passed across a subject of interest (such as a human patient) and a portion of the radiation strikes a detector that collects image data. In a digital X-ray system, a photodetector produces a signal representing the amount or intensity of radiation striking a discrete pixel area of ​​the detector surface. The signal can then be processed to generate an image that can be displayed for viewing. In the images produced by such a system, it is possible to identify and examine internal structures and organs inside the patient's body. In a CT imaging system, as the gantry rotates around the patient, a detector array, which includes a series of detector elements or sensors, etc., produces similar signals through various locations, allowing volume reconstruction to be obtained.

[0003] Accurate three-dimensional (3D) measurements of a patient during CT can significantly improve subsequent workflows (eg, patient positioning, automatic calibration, etc.) For example, using 3D measurements of a patient and position information obtained from the measurements can help determine patient movement. Summary of the invention

[0004] The following summarizes certain embodiments commensurate with the scope of the initially claimed subject matter. These embodiments are not intended to limit the scope of the claimed subject matter, but these embodiments are only intended to provide a brief overview of the possible forms of the subject matter. In fact, the subject matter may include a variety of forms, which may be similar to or different from the embodiments described below. The present disclosure introduces the concepts described in more detail in the specific embodiments. It should not be used to determine the essential characteristics of the claimed subject matter, nor should it be used to limit the scope of the claimed subject matter.

[0005] In one aspect, a method for identifying movement of a patient during a medical imaging scan includes: initiating motion detection data acquisition; initiating a medical imaging scan of the patient to acquire scan data; determining a motion score curve for a duration of the medical imaging scan based on the motion detection data; removing portions of the scan data corresponding to a motion score curve outside an acceptable range; and selecting the scan data corresponding to the motion score curve within the acceptable range for reconstruction.

[0006] On the other hand, a medical imaging system is provided. The medical imaging system includes a computed tomography (CT) imaging system, the CT imaging system including: a gantry having an aperture and capable of rotating about a rotation axis; an X-ray source mounted on the gantry and configured to emit an X-ray beam; an X-ray controller for operating the X-ray source; and an X-ray detector configured to detect the X-ray beam emitted by the X-ray source. The medical imaging system also includes a motion detection system coupled to the CT imaging system, the motion detection system including: a motion detection device mounted on the gantry; a controller for controlling the operation of the motion detection device; and a mobile data processing unit for obtaining data from the motion detection device, wherein the mobile data processing unit obtains a baseline position of a patient and real-time movement data during an imaging scan to generate additional position information, wherein the real-time movement data is compared with the baseline position of the patient. The system also includes a processor for determining a motion score of the patient for each view during the scan, and selecting views of the scan data corresponding to motion scores within an acceptable range for image reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] These and other features, aspects, and advantages of the disclosed subject matter will be better understood when the following detailed description is read with reference to the accompanying drawings, in which like characters refer to like parts throughout the several views, and in which:

[0008] Figure 1 is a graphical representation of a CT imaging system according to aspects of the present disclosure;

[0009] Figure 2 According to various aspects of the present disclosure Figure 1 Block diagram of the CT imaging system in;

[0010] Figure 3 is a schematic diagram of a motion detection system window placement within a gantry of a CT imaging system according to aspects of the present disclosure;

[0011] Figure 4 is a perspective view of a schematic diagram of a motion detection system relative to a patient on a CT table in accordance with aspects of the present disclosure;

[0012] FIG. 5A to FIG. 5C depicts a single motion detection device that obtains data at different angular positions in accordance with aspects of the present disclosure;

[0013] Figure 6 is a pictorial representation of a single motion detection device rotating 360 degrees around a patient for data acquisition in accordance with aspects of the present disclosure;

[0014] Figure 7 is a pictorial representation of a plurality of motion detection devices rotating about a patient for data acquisition in accordance with aspects of the present disclosure;

[0015] Figure 8 is a perspective view of a schematic diagram of multiple motion detection devices simultaneously acquiring patient data at different angular positions in accordance with aspects of the present disclosure;

[0016] Fig. 9 is a pictorial representation of a plurality of motion detection devices positioned 360 degrees around a patient for data collection in accordance with aspects of the present disclosure;

[0017] Fig.10 is a pictorial representation of an external motion detection system coupled to a CT table in accordance with aspects of the present disclosure;

[0018] Fig.11 is a flow chart of a method for motion-guided retrospective gating in a CT imaging system;

[0019] Fig.12 is with Fig.11 A flowchart of a method for processing patient movement data used in conjunction with the method;

[0020] Fig.13 is with Fig.11 A flowchart of the method for performing retrospective gating used in conjunction with the method;

[0021] Fig.14 are illustrative examples of selected surface regions of interest to be monitored for motion during scanning;

[0022] Fig.15 An example range of acceptable motion during scanning is depicted;

[0023] FIG. 16A to FIG. 16C depicts an example data set depicting acceptable and unacceptable motion during a scan; and

[0024] FIG. 17A to FIG. 17E Depicted are examples of scan data that may be selected based on retrospective gating. DETAILED DESCRIPTION

[0025] Embodiments of the present disclosure will now be described by way of example with reference to the accompanying drawings. In order to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be understood that in the development of any such actual implementation, as in any engineering or design project, many implementation-specific decisions must be made to achieve the developer's specific goals, such as complying with system-related and business-related constraints that may vary from implementation to implementation. In addition, it should be understood that such development efforts may be complex and time-consuming, but are still routine tasks for design, fabrication, and manufacturing for those of ordinary skill who benefit from the present disclosure.

[0026] When introducing elements of various embodiments of the present subject matter, the articles "a," "an," "the," and "said" are intended to indicate that there are one or more elements. The terms "comprising," "including," and "having" are intended to be inclusive, and mean that additional elements may be present in addition to the listed elements. Furthermore, any numerical examples in the following discussion are intended to be non-limiting, and thus the additional numerical values, ranges, and percentages are within the scope of the embodiments disclosed herein.

[0027] Although the various aspects discussed below can be provided in the context of medical imaging, it should be understood that the present technology is not limited to such medical contexts. In fact, providing examples and explanations in such medical contexts is only to facilitate explanation by providing examples of reality specific implementation and application. However, the present method can also be used in other contexts, such as for the tomographic image reconstruction of industrial computer tomography (CT) used in the non-destructive inspection (i.e., quality control or quality audit application) of finished parts or finished products and / or the non-invasive inspection (i.e., security inspection or screening application) of packages, boxes, luggage, etc. In general, the present method can be used to provide accurate three-dimensional (3D) information of the target in any imaging or screening context to improve the workflow process and post-processing steps.

[0028] The present disclosure provides systems and methods for monitoring patient motion during CT scanning, which may include combining laser imaging, detection and ranging (LiDAR)-based technology, motion sensors and / or 3D cameras with CT imaging systems. Example motion detection systems include LiDAR systems, which are remote sensing methods for measuring target objects or patients at variable distances from an X-ray source. With the advancement of LiDAR technology, it can now produce 3D renderings of subjects with high spatial resolution (e.g., sub-millimeter (mm) accuracy). The disclosed motion detection technology using LiDAR technology uses the time-of-flight information of reflected pulsed light (e.g., laser) to calculate and reproduce the patient's 3D information (e.g., depth-related information). The time-of-flight information can calculate depth, which can be used to create a 3D model of a patient undergoing a CT scan and to detect the motion of a patient undergoing a CT scan. Multiple views are used to cover the entire target area to reproduce high-fidelity 3D information. In certain embodiments, light images can be collected by moving a data acquisition system (i.e., a LiDAR scanning system with one or more LiDAR scanners or instruments) around a target (e.g., around a gantry). Using these techniques, a LiDAR-based motion detection system can accurately detect the patient's motion in real time. Additionally or alternatively, other types of motion sensors and / or 3D cameras can be used to track the patient's motion. For example, a motion detection system using a 3D camera (e.g., a depth camera) can create a 3D mesh that can be updated in real time to monitor the patient's movement.

[0029] In some embodiments, the motion detection system is integrated into the CT imaging system. In this embodiment, the data acquisition system can be integrated outside the scanning window (and therefore physically coupled to the CT imaging system) and rotated to capture multiple views. In some embodiments, multiple motion detection devices or instruments can be placed at different angular positions around the patient to capture the entire region of interest. In some embodiments, the motion detection system (e.g., with multiple motion detection devices or instruments) can be installed externally relative to the frame (e.g., on the scanner housing or CT table), but still physically coupled to the CT imaging system. The external motion detection system can be placed in an appropriate position according to the needs of the rail system. Patient movement data can be collected before, during and after the CT scan of the target or patient. Patient movement data can be processed and used for subsequent (i.e., after LiDAR scanning) workflow processes (e.g., accurate light reconnaissance measurements, appropriate patient positioning and automatic calibration, etc.) and post-processing steps (e.g., image reconstruction). The disclosed embodiment provides an overall framework for including a motion detection system in a CT imaging system to improve the overall efficiency and robustness of the workflow process and post-processing steps.

[0030] The present disclosure also provides a method for detecting the position and movement of an object or patient positioned for imaging scanning using a motion detection system. An example motion detection system provides data related to the position and movement of an object, specifically 3D point cloud information or 3D mesh information of the object or patient. The position and movement information data can be compared with an imaging protocol to determine whether the position or movement of the object corresponds to the protocol (i.e., the right portion of the object is positioned to be imaged, and the movement of the patient is within an acceptable range to provide high-quality scan data). If movement outside the acceptable range is detected, the imaging system can resolve the movement by removing views from the imaging scan that includes the movement. Specifically, the imaging system can select only continuous portions of data with movement within the acceptable range for use during reconstruction, and discard data containing movement that falls outside the acceptable range. Therefore, image quality can be improved by eliminating movement of the subject.

[0031] Taking into account the foregoing and referring to Figure 1 and Figure 2 , a CT imaging system 10 is shown by way of example. The CT imaging system 10 includes a gantry 12 enclosed in a housing 13 (e.g., a gantry housing). The gantry 12 has a rotating component and a fixed component. The gantry 12 has an X-ray source 14 that projects a beam of X-rays 16 toward an X-ray detector assembly or an X-ray detector array 15 (e.g., having a plurality of detector modules) on the opposite side of the gantry 12. The X-ray source 14 and the X-ray detector assembly 15 are disposed on the rotating portion of the gantry 12. The X-ray detector assembly 15 is coupled to a data acquisition system (DAS) 33. The plurality of detector modules of the X-ray detector assembly 15 detect the projected X-rays that pass through a patient or subject 22, and the DAS 33 converts the data into digital signals for subsequent processing. Each detector module of the X-ray detector assembly 15 in a conventional system generates an analog electrical signal that represents the intensity of the incident X-ray beam and, therefore, the intensity of the attenuated X-ray beam when the incident X-ray beam passes through the patient 22. During a scan to acquire x-ray projection data, the gantry 12 and components mounted thereon are rotated about a center of rotation 24 (eg, isocenter) to collect attenuation data from multiple viewing angles relative to the imaging volume.

[0032] The rotation of the gantry 12 and the operation of the x-ray source 14 are controlled by a control mechanism 26 of the CT imaging system 10. The control mechanism 26 includes an x-ray controller 28 that provides power and timing signals to the x-ray source 14 and a gantry motor controller 30 that controls the rotational speed and position of the gantry 12.

[0033] The imaging system 10 also includes a motion detection system 32 physically coupled to the imaging system 10. In some examples, the motion detection system includes a LiDAR system and / or a 3D camera. The motion detection system 32 includes one or more motion detection devices or instruments 34. As depicted, the motion detection system 32 has a motion detection device 34. One or more motion detection devices 34 are used to collect depth-related information (e.g., LiDAR data or light images, 3D mesh data) of the patient 22 with high spatial fidelity. The depth-related information is utilized in the subsequent workflow process for CT scanning. In an example in which LiDAR technology is used, one or more motion detection devices 34 emit pulsed light 35 (e.g., laser) at the patient 22 and detect the pulsed light reflected from the patient 22. The motion detection system 32 is configured to collect movement data from multiple different views (e.g., at different angular positions relative to the rotation axis 24).

[0034] In certain embodiments, such as Figure 1 and Figure 2 As depicted in FIG. 1 , a motion detection device 34 is coupled to the gantry 12. Specifically, the motion detection device 34 is disposed outside the scanning window within the gantry housing 13. The motion detection device 34 rotates around the patient 22 to collect movement data at different angular positions. In some embodiments, multiple motion detection devices 34 may be coupled to the gantry 12 and rotated to collect movement data at different angular positions.

[0035] In certain embodiments, multiple motion detection devices 34 may be coupled to the frame 12 in fixed positions, but disposed at different angular positions (e.g., relative to the rotation axis 24). In the illustrated example, the motion detection device 34 is depicted as a LiDAR scanner, but other suitable means of detecting motion (e.g., 3D cameras, sensors, etc.) may be used in addition to and / or in lieu of a LiDAR scanner. The motion detection device 34 in a fixed position may collect movement data while remaining stationary.

[0036] In some embodiments, the motion detection system 32 can be located outside the gantry 12, but still physically coupled to the imaging system 10. For example, multiple motion detection devices 34 can be coupled to a panel (e.g., at different angular positions relative to the rotation axis 24), which is coupled to a rail system. The rail system can be coupled to the gantry housing 13 or the table 36 of the system 10. The rail system can be configured to move the panel toward and away from the gantry 12. In some embodiments, the rail system can also be configured to rotate the panel about the rotation axis 24.

[0037] The motion detection system 32 includes a controller 38 configured to provide timing and control signals to one or more motion detection devices 34 for collecting motion data at different angular positions. The motion data can be collected before, during and / or after the CT scan of the patient 22. The motion detection system 32 also includes a motion data processing unit 40 that receives or obtains the motion data from the one or more motion detection devices 34. The integrated motion detection system and / or the motion data processing unit 40 utilizes the flight information time of the reflected pulsed light and processes the motion data (e.g., collected at different views) to generate accurate 3D measurements of the patient 22. The 3D measurements of the patient 22 have high spatial resolution (e.g., sub-millimeter accuracy). As described above, the 3D measurements can be used in the subsequent workflow process of the CT scan. For example, the 3D measurements can be used as accurate light reconnaissance measurements (e.g., for modifying scan acquisition parameters). The 3D measurements can also be used for proper patient positioning (e.g., for modifying or optimizing patient position parameters) and automatic calibration. The 3D measurements can also be used for post-processing, such as image reconstruction algorithms for CT scan data (e.g., modifying reconstruction parameters).

[0038] 3D measurement information from the motion detection system 32 (e.g., from the mobile data processing unit 40) and the scan data from the DAS 33 are input to a computer 42. The computer 42 includes a calibration vector storage device 44 (e.g., for storing calibration parameters and calibration protocols used to acquire CT scan data). The 3D measurement information obtained from the motion detection system 32 can be used to determine the calibration parameters utilized. The computer 42 also includes a data correction unit 46 for processing or correcting the CT scan data from the DAS 33. The computer 42 also includes an image reconstructor 48. The image reconstructor 48 receives sampled and digitized X-ray data from the DAS 33 and performs high-speed reconstruction. The reconstructed image is applied as input to the computer 42, which stores the image in a mass storage device 50. The computer 42 also receives commands and scan parameters from an operator through a console 52. An associated display 54 allows the operator to observe the reconstructed image as well as the 3D measurement data and other data from the computer 42. Computer 42 uses operator provided commands and parameters to provide control signals and information to DAS 33, X-ray controller 28, gantry motor controller 30, and controller 38. In addition, computer 42 operates table motor controller 56, which controls the motorized table 36 to position patient 22 relative to gantry 12. Specifically, table 36 moves portions of patient 22 through gantry opening or aperture 58.

[0039] The computer 42 and the mobile data processing unit 40 may each include a processing circuit. The processing circuit may be one or more general or special purpose microprocessors. The processing circuit may be configured to execute instructions stored in a memory to perform various actions. For example, the processing circuit may be used to receive or obtain mobile data collected by the motion detection system 32. In addition, the processing circuit may also generate 3D measurements of the patient 22. In addition, the processing circuit may utilize the 3D measurements in a subsequent workflow process for a CT scan of the patient performed by the CT imaging system 32.

[0040] Figure 3 Schematic diagram of the placement of the motion detection system window within the gantry 12 of the CT imaging system. The gantry 12 includes a gantry cover 60, which is configured to be located on the front of the gantry housing adjacent to the CT table and on the rear of the gantry housing. The CT imaging system includes an annular scanning window 62 disposed within an inner wall 64 of the gantry 12, which is formed within an opening or aperture 58 of the gantry 12. The scanning window 62 is made of an X-ray transparent material that enables X-rays emitted from an X-ray source to pass through an object or subject being imaged so as to be detected by a detector. The scanning window 62 is configured to fit between components (e.g., a front cover and a rear cover) of the housing of the gantry 12 to fill the gap. During an imaging session, the subject or patient moves within the aperture 58. The scanning window 62 is self-supporting and acts as a safety barrier to prevent the subject or patient from contacting rotating components within the gantry 12.

[0041] As depicted, an annular motion detection system panel or window 66 is also disposed within the inner wall 64 of the gantry 12 formed within the aperture 58 of the gantry 12. The panel 66 is made of a material transparent to pulsed light (e.g., laser light) emitted by one or more motion detection devices disposed within the gantry 12 toward the object or subject and reflected back to the one or more motion detection devices. The panel 66 is disposed between the scan window 62 and the gantry cover 60 in the Z direction. Specifically, the panel 66 is disposed between the scan window 62 and the front of the gantry 12 adjacent to the CT table. During the imaging session, the subject or patient moves within the aperture 58. The panel 66 is also self-supporting and acts as a safety barrier to prevent the subject or patient from contacting components (e.g., sometimes rotating components) within the gantry 12. One or more motion detection devices may be located behind the panel 66 within the gantry 12. In some embodiments, the one or more motion detection devices 34 are fixed during the acquisition of the motion data. In some embodiments, the one or more motion detection devices rotate during the acquisition of the motion data. Panel 66 is located outside the area of ​​the subject or object being scanned by the CT imaging system.

[0042] Figure 46 is a perspective view of a schematic diagram of a motion detection system 32 relative to a patient on a CT table 36. In addition to the motion detection system 32, components of the gantry are not shown for simplicity. One or more motion detection devices 34 may be coupled to a panel or window 66. As depicted, a single motion detection device 34 is coupled to the panel 66. In some embodiments, multiple motion detection devices 34 may be disposed at different circumferential locations along the panel 66 (e.g., relative to the patient). Figure 2 The panel 66 is disposed within an inner wall of the frame formed within an aperture of the frame. The motion detection device 34 is arranged concentrically with the panel 66 (e.g., relative to the rotation axis 24), wherein the panel 66 is positioned radially closer (in the Y direction) to the rotation axis 24 than the motion detection device 34. In some embodiments, the panel 66 and the associated motion detection device 34 remain in a fixed position while the motion detection device 34 collects movement data at different angular positions. In some embodiments, the panel 66 and one or more associated motion detection devices 34 rotate to collect movement data.

[0043] FIG. 5A to FIG. 5C A single motion detection device 34 is depicted that obtains data at different angular positions. Other than the motion detection system 32, components of the housing are not shown for simplicity. FIG. 5A to FIG. 5C As depicted in FIG. 6 , a single motion detection device 34 is coupled to a panel 66. The motion detection device 34 rotates (e.g., around Figure 2 The motion detection device 34 (and the panel 66) is rotated to different angular positions to collect different views of the motion data. The data collected at the different angular positions can then be combined to generate 3D measurements of the patient 22. It should be noted that although the patient 22 is depicted as being outside the area of ​​the rack where the panel 66 is located, in some embodiments, the patient 22 can be moved into the rack by the workbench 36 so that the panel 66 is disposed around a portion of the patient 22. Figure 6 As depicted in , a single motion detection device 34 may be rotated up to 360 degrees about a target (ie, patient 22 ) in a circumferential direction 70 (eg, relative to axis of rotation 24 ) to collect movement data at different angular positions.

[0044] In certain embodiments, such as Figure 7, multiple motion detection devices 34 may be coupled to panel 66. As depicted, two motion detection devices 34 are coupled to panel 66. The number of motion detection devices 34 coupled to panel 66 may vary (e.g., 2, 3, 4, 5, 6, or another number of motion detection devices 34). The motion detection devices 34 are spaced apart from one another on circumference 70 along panel 66. Each motion detection device 34 (and panel 66) rotates about axis of rotation 24. In some embodiments, each motion detection device 34 rotates only a portion of the 360 ​​degrees around patient 22 to collect movement data. For example, as Figure 7 , each motion detection device 34 may only rotate up to about 180 degrees on the circumference 70. Thus, two motion detection devices 34 together may cover 360 degrees around the patient 22. In some embodiments, where three motion detection devices 34 are coupled to the panel 66, each motion detection device 34 may cover up to about 120 degrees on the circumference 70. In some embodiments, where four motion detection devices 34 are coupled to the panel 66, each motion detection device 34 may cover up to about 90 degrees on the circumference 70. Thus, regardless of the number of motion detection devices 34 coupled to the panel 66, each motion detection device 34 may cover an equal portion of the 360 ​​degrees around the patient 22. In some embodiments, when multiple motion detection devices 34 are coupled to the panel 66, one or more of the motion detection devices 34 may cover a different angular range around the patient 22 relative to the other motion detection devices 34. For example, in the case of two motion detection devices 34, one motion detection device 34 may cover 120 degrees, and the other motion detection device may cover 240 degrees. In some embodiments, when multiple motion detection devices 34 are coupled to the panel 66, each motion detection device 34 may cover up to 360 degrees to provide redundancy in the acquired data. In some embodiments, the motion detection system 32 may not cover 360 degrees around the patient 22 when certain angular positions are blocked (e.g., blocked by the bottom of the CT table).

[0045] Figure 8 and Fig. 9It is shown that multiple motion detection devices 34 are used to obtain data of the patient 22 at different angular positions at the same time. In addition to the motion detection system 32, the components of the rack are not shown for simplicity. As depicted, the motion detection system 32 includes multiple motion detection devices 34 coupled to the panel 66. The motion detection devices 34 are spaced apart from each other on the circumference 70 along the panel 66 (for example, relative to the rotation axis 24). The motion detection devices 34 are arranged at fixed positions (for example, different angular positions) along the panel 66. Both the motion detection devices 34 and the panel 66 remain fixed during the acquisition of the mobile data. Specifically, the mobile data is collected by each of the motion detection devices 34 scanners at the same time, thus providing mobile data at different views (that is, different angular positions). The data collected at different angular positions can then be combined to generate 3D measurements of the patient 22.

[0046] In certain embodiments, the motion detection system 32 may be located external to the gantry 12 , yet still physically coupled to the imaging system 10 . Fig.10 is a pictorial representation of an external motion detection system 32 coupled to a CT table 36. The motion detection system 32 is coupled to a rail system 72. The rail system 72 is coupled to the table 36. The rail system 72 is configured to move the motion detection system 32 toward and away from the gantry 12 (e.g., in the Z direction along the longitudinal length of the patient 22). The rail system 72 includes a main rail 74 coupled to a support structure 76 that supports the main rail 74. The main rail 74 extends in the Z direction above the table 36 (e.g., along the longitudinal length of the table 36). The support structure 76 is coupled to the table 36. The support structure 76 extends from the table 36 in a vertical direction (e.g., in the Y direction) and then extends in a horizontal direction (e.g., in the X direction) to couple to the main rail 74. The configuration of the support structure 76 and the manner in which it is coupled to both the table 36 and the main rail 74 can vary.

[0047] The motion detection system 32 includes a panel 68 (e.g., having an arcuate shape). The panel 68 includes a plurality of motion detection devices coupled thereto. The plurality of motion detection devices are spaced circumferentially along the arc of the panel 68 at different angular positions to enable different views of motion data to be collected. The panel 68 is coupled to a rail system 72. Specifically, the panel 68 is coupled to a main rail 74 via vertical support struts 76 (e.g., columns or bars). The rail system 72 is configured to enable the panel 68 (and the vertical support struts) to move back and forth along the main rail 74 toward the frame 12 as indicated by arrow 78 (in the Z direction). The main rail 74 may include an actuation system (e.g., a chain actuator, an electromechanical linear actuator, or any other mechanism for facilitating linear movement along the main rail 74). In certain embodiments, the rail system 72 is configured to enable the panel 68 to move circumferentially along its arc. Specifically, the rail system 72 may enable the panel 68 to rotate circumferentially (e.g., relative to the axis of the vehicle). Figure 2 The panel 68 is rotatable in a clockwise and counterclockwise direction (e.g., relative to the vertical support strut 76). Figure 2 The rotational movement of the panel 68 enables the acquisition of movement data from additional different angular positions.

[0048] Fig.11 A flow chart of a method 1100 for retrospective gating based on motion detected during scan data acquisition is depicted. The method begins at block 1102 with patient setup (including positioning on the table 36 of the CT imaging system 10) and initial entry or confirmation of patient data in a graphical user interface of the CT system (e.g., Fig.14 ). In some examples, a user or technician assists in placing the patient on the table. In other examples, the patient may position themselves on the table with the assistance of a technician and / or the imaging system. Patient setup may also include the CT imaging system obtaining a scan protocol. For example, a computer 42 associated with the CT imaging system obtains the scan protocol from a mass storage device 50, a remote server, and / or patient information. At box 1104, patient movement monitoring and data acquisition begins. Patient movement monitoring and data acquisition may include the use of any suitable motion detection system, including but not limited to LiDAR systems, 3D cameras, and other motion detectors. Monitoring and data acquisition are performed continuously and in real time for the duration of the scan.

[0049] At block 1106, a scan is initiated and patient scan data acquisition begins. During the patient scan, scan data and movement data are acquired simultaneously (blocks 1108 and 1110). Additionally, the movement data may be processed in real time to determine a motion score. Fig.12Further details of an example method for processing patient motion monitoring data are described in block 1112. In block 1112, the data is used to perform retrospective gating that removes portions of the scan data that contain motion above a threshold. Fig.13 The described method provides more details about retrospective gating. After the retrospective gating is completed, the method 1100 continues to perform image reconstruction using the remaining scan data. The image reconstruction can include any known reconstruction method suitable for use with CT scan data. After reconstruction, the method 1100 is completed.

[0050] Fig.12 A flow chart of a method 1200 for determining a motion score based on movement data is depicted. The method 1200 begins with real-time patient movement monitoring data acquisition to collect movement data of the patient. Movement data is collected over the entire duration of the CT scan (box 1202). When the scan and data acquisition are complete (box 1204), a motion score is calculated (box 1206). The motion score is a quantitative measure that can be used to determine whether the patient's movement during the scan exceeds a threshold. The motion score is then embedded in the scan data (box 1206). That is, the motion score is calculated for each time point of the scan and synchronized with the scan data so that the motion score can be identified at each point in the scan. The scan data with the embedded motion score is saved for later use by the user (box 1210), and the method 1200 is completed.

[0051] Fig.13 A flow chart of a method 1300 for retrospectively gating views of a scan that include excessive motion is depicted. The method 1300 begins by obtaining scan data with an embedded motion score (block 1302). Fig.16AAn example scan data set with motion scores embedded therein is depicted. An example motion score may be depicted in the form of a motion score curve indicating the amount of motion at each time point during the scan (block 1304). The example motion score curve is presented to a user or technician via a graphical user interface. According to the motion curve, views with excessive motion are identified based on the motion score associated with each view. For example, any point on the curve depicting a motion score outside of an acceptable motion score is identified, and a view with acceptable motion is selected (block 1306). In some examples, views with excessive motion are identified, and the remaining views are initially automatically selected (e.g., by a data correction unit) for reconstruction. Alternatively, the view may be manually selected by a user or technician. If the selection of views with acceptable motion should be modified (block 1308), the user may manually identify and / or remove views with excessive motion and select views with acceptable motion. The user may use a graphical user interface to change the selection. If the selection does not need to be modified, the method continues to block 1310, where the selection is confirmed by the user or technician. The selection is then provided to an image reconstructor for image reconstruction 1312. The method 1300 is completed.

[0052] Fig.14 An example user interface 1400 of a patient setup is depicted, where the chest of patient 22 is to be scanned. Surface areas of interest are represented by dashed lines 1402. These lines 1402 can be adjusted based on the size of patient 22 and can be used to ensure that the correct area of ​​interest is scanned. Additionally, patient information and scan protocol information are displayed so that the user can confirm the information or adjust the information if necessary. Scanning can also be initiated from the user interface.

[0053] Fig.15 An example representation of determining a motion score for a patient's profile is depicted. The patient's initial or neutral state 1502 may be represented by t0. Different amounts of motion are represented by profiles 1504 and 1506 (i.e., t1 and t2). For example, motions t1 and t2 may be the result of chest movement due to the patient's breathing, or may be the result of a sudden, large movement of the patient. Specifically, motions that may fall outside of an acceptable range may be the result of unexpected patient movement rather than the result of repeatable, cyclical motion of the patient's breathing. A motion score may be calculated for each movement to determine whether the movement falls outside of an acceptable range of motion. For the patient's profiles 1502, 1504, 1506, a motion score may be calculated using Equation 1:

[0054] Equation 1:

[0055] In Equation 1, a motion score can be determined for each contour at a certain point in time during the scan. nCompared to the initial or baseline position t0, where n represents the number of the time point or profile 1504, 1506 being evaluated. The total motion score is determined using the position of the profiles 1504, 1506 in both the x and y directions. In addition to the magnitude, the direction of the motion score can also be given. For example, the motion score of profile 1504 may be negative because the movement is a decrease in the y direction from the initial profile 1502, and the motion score of 1506 may be positive because the movement is an increase in the y direction from the initial profile 1502. The position of the patient can be determined based on a point cloud or data grid created using the movement data collected using the motion detection device. For example, if one or more of these motion detection devices includes a LiDAR scanner, a 3D point cloud can be created to identify the position of the patient at any given time during the scan, and the patient's real-time position or movement data can be compared with the patient's initial position or initial point cloud information to determine the motion score. Similarly, if the motion detection device includes a 3D camera, the 3D grid created by the camera can be compared to the initial or baseline 3D grid in real time to determine the motion score. Thus, a motion score for each view is determined based on the initial position information and real-time or additional position information obtained for the duration of the scan.

[0056] For the patient's surface, the motion score can be calculated using Equation 2:

[0057] Equation 2:

[0058] To obtain a motion score for the patient surface, Equation 2 also incorporates a z-direction component. The motion score can be calculated for the entire surface of interest of the patient at each time point for the duration of the scan. The motion score is then embedded in the scan data and provided to the user in a graphical representation of a curve indicating which views have motion scores exceeding an acceptable threshold.

[0059] FIG. 16A to FIG. 16C An example graphical representation of a curve 1602 indicating motion scores throughout a scan is depicted. Fig.16A As shown, the motion score fluctuates over the duration of the scan region 1604 and the post-scan region 1606 of the graph. During the pre-scan region 1612 or preparation region of the graph, motion data acquisition begins at time 1608 just prior to the scan data acquisition start time 1610. While this example depicts motion data acquisition continuing after the scan is complete 1614, motion data acquisition may also end at the end of the scan data acquisition.

[0060] Fig. 16B An example graph is depicted including an acceptable motion score range 1616 and an unacceptable motion score range 1618. For example, when the motion score exceeds a threshold, the motion score enters an unacceptable range. Fig. 16B As depicted in FIG. 1 , a portion 1620 of the scan view corresponds to a motion score that exceeds a threshold and falls within an unacceptable range 1618. This portion 1620 is identified as unacceptable, and the remaining portion of the scan view, or an acceptable portion 1622, is selected for image reconstruction, as shown in FIG. Fig. 16C For some scans (such as axial scans), the remaining portion of the scan data must meet a threshold length to be sufficient for reconstruction. For example, the continuous length of an acceptable portion of the data must have a length of at least two-thirds of the scan duration.

[0061] FIG. 17A to FIG. 17E Additional samples of motion data during the scan are depicted. Fig.17A and Fig. 17B An example motion data set is depicted that includes a portion of a view having a motion score that exceeds an acceptable range near the start of a scan. This data set may be accepted for reconstruction because the acceptable scan data has a shorter scan than the minimum ( Fig.17A ) long length and has a maximum short scan range that avoids extreme motion greater than two-thirds of the scan duration. Fig. 17C Also depicted are data sets that are acceptable for reconstruction because the acceptable data have a run-length longer than a minimum short scan (eg, two-thirds of the duration of the total scan). Fig.17D Scan data is depicted that includes more motion overall (eg, the motion score fluctuates more than previously depicted scan data sets), but much of the motion is still within acceptable ranges and an acceptable portion of the data is sufficient for reconstruction.

[0062] Fig.17E Depicted is not sufficient example data set to build on. Fig.17E In the example above, the portion of the data corresponding to motion scores outside the acceptable range is in the middle of the scan duration. Therefore, both portions of the scan data corresponding to acceptable motion scores are not long enough for reconstruction. After seeing the motion scores for this data set, the user or technician will restart the scan to obtain a data set that is acceptable for reconstruction.

[0063] Although an example method as a whole is described, portions of the method may be used independently of the remainder of the method. In other examples, other portions of methods 1100, 1200, and 1300 may be excluded, or additional steps may be included and / or repeated. Although a CT system is described by way of example, it should be understood that the present technology may also be useful when applied to images acquired using other imaging modalities, such as X-ray imaging systems, magnetic resonance (MR) imaging systems, positron emission tomography (PET) imaging systems, single photon emission computed tomography (SPECT) imaging systems, ultrasound imaging systems, and combinations thereof (e.g., multimodal imaging systems, such as PET / CT, PET / MR, or SPECT / CT imaging systems). The present discussion of the CT imaging modality is provided merely as an example of a suitable imaging modality.

[0064] Technical effects of the disclosed embodiments include providing systems and methods for generating accurate representations of a patient's movement during a CT scan to be utilized during a subsequent CT workflow for the CT scan. The present disclosure provides systems and methods for combining motion detection technology (which may include LiDAR-based technology) with a CT imaging system to more efficiently assist in various workflows. The disclosed embodiments provide a method for detecting movement of a subject during an imaging scan and then selecting a scan view containing an acceptable amount of movement based on the detected movement to improve image quality.

[0065] Reference is made to the technology presented and claimed herein and applied to physical and specific examples of a practical nature that clearly improves upon the present state of the art and, therefore, is not abstract, intangible, or purely theoretical. In addition, if any claim appended to the end of this specification contains one or more elements designated as "means for [performing] the function of ..." or "steps for [performing] the function of ...," it is intended that such elements be interpreted under 35 U.S.C. § 112(f). However, for any claim containing elements designated in any other manner, it is not intended that such elements be interpreted under 35 U.S.C. § 112(f).

[0066] This written description uses examples to disclose the subject matter, including the best mode, and also enables those skilled in the art to practice the subject matter, including making and using any device or system and performing any included method. The patent scope of the subject matter is defined by the claims and may include other examples that occur to those skilled in the art. Such other examples are intended to fall within the scope of the claims if they have structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are slightly different from the literal language of the claims. The embodiments of the present disclosure shown in the drawings and described above are merely exemplary embodiments and are not intended to limit the scope of the appended claims, including any equivalents included within the scope of the claims. Various modifications are possible and will be apparent to those skilled in the art. It is intended that any combination of non-mutually exclusive features described herein is within the scope of the present invention. That is, the features of the embodiments may be combined with any appropriate aspect described above, and the optional features of any one aspect may be combined with any other appropriate aspect. Similarly, the features listed in the dependent claims may be combined with the non-mutually exclusive features of other dependent claims, especially where the dependent claims are dependent on the same independent claim. In some jurisdictions requiring single claim dependencies, it may be practice to use such dependencies, but this should not be taken to mean that the features in the dependent claims are mutually exclusive.

Claims

1. A method of identifying movement of a patient during a medical imaging scan, the method comprising: Initiate motion detection data collection; initiating a medical imaging scan of the patient to acquire scan data; determining a motion scoring curve for a duration of the medical imaging scan based on the motion detection data; removing portions of the scan data corresponding to a motion score curve outside an acceptable range; and The scan data corresponding to the motion score curve within the acceptable range is selected for reconstruction. 2 . The method of claim 1 , wherein the motion score curve is a compilation of motion scores calculated for each view for the duration of the scan. 3 . The method of claim 2 , further comprising determining a baseline position of the patient for determining the motion score for each view. The method of claim 1 , wherein the motion score curve is determined for a contour of the patient. The method of claim 1 , wherein the motion scoring curve is determined for a surface of the patient. 6 . The method according to claim 1 , wherein the selection of the scan data corresponding to the motion score curve within the acceptable range is automatically determined by a data correction unit, and wherein a user confirms the selection.

7. The method of claim 1, wherein the motion detection data acquisition uses one or more motion detection devices to detect motion in real time during the scanning.

8. The method of claim 7, wherein the motion detection device comprises at least one of a LiDAR scanner and a 3D camera.

9. A medical imaging system, comprising: A computer tomography (CT) imaging system, the CT imaging system comprising: a frame having an aperture and being rotatable about a rotation axis; an X-ray source mounted on the gantry and configured to emit an X-ray beam; An X-ray controller for operating the X-ray source; and an X-ray detector configured to detect the X-ray beam emitted by the X-ray source; A motion detection system, the motion detection system being coupled to the CT imaging system, wherein the motion detection system comprises: a motion detection device, the motion detection device being mounted on the rack; a controller for controlling the operation of the motion detection device; and a motion data processing unit for obtaining data from the motion detection device, wherein the motion data processing unit obtains a baseline position of a patient and real-time motion data during an imaging scan to generate additional position information, wherein the real-time motion data is compared to the baseline position of the patient; and A processor is configured to determine a motion score of the patient for each view during the scan and select a view of the scan data having the corresponding motion score within an acceptable range for image reconstruction.

10. The system of claim 9, further comprising determining a motion score curve from a compilation of the motion scores calculated for each view for the duration of the scan.

11. The system of claim 9, wherein the motion score is based on the baseline position of the patient and the real-time movement data corresponding to each view during the scan.

12. The system of claim 9, wherein the motion score is determined for a contour of the patient.

13. The system of claim 9, wherein the motion score is determined for a surface of the patient.

14. The system of claim 9, wherein the processor comprises a data correction unit for automatically selecting the view of the scan data corresponding to the motion score within the acceptable range.

15. The system of claim 9, wherein the motion detection device comprises at least one of a LiDAR scanner and a 3D camera.

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