Method and system for automatic positioning of scanned objects

Abstract

Methods and systems are disclosed for automated positioning of scanned objects in medical imaging. The method comprises the following steps: acquiring scanning information of a to-be-imaged scanning object to determine scanning features of the scanning object; identifying a corresponding offset characterization value in a mapping table between the scanning features and the offset characterization values based on the scanning features of the scanning object; and adjusting the target position of the scanning object in the automatic positioning of the scanning object based on the corresponding offset representation value.

Description

Technical Field

[0001] The present invention relates to the technical field of medical imaging systems, and in particular to a method and system for automatically positioning a scanned object. The present invention also particularly relates to a processor for executing the above method and a computer-readable storage medium storing a computer program capable of implementing the above method. Background Art

[0002] Non-invasive radiological imaging techniques allow images of the internal structures of a scanned object (usually including a patient) to be obtained without performing invasive procedures on the scanned object. Specifically, techniques such as computed tomography (CT) use various physical principles (such as differential transmission of X-rays through a target volume) to acquire image data and construct tomographic images (e.g., a three-dimensional representation of the interior of a human body or other imaging structure). In a modern CT imaging system, a gantry includes a donut-shaped frame having an x-ray tube on one side and a detector on the other opposite side, the frame rotating around a patient positioned on a table, thereby generating thousands of cross-sectional views of the patient in one scan. In order to effectively use these imaging techniques and obtain good image quality, the scanned object must be properly positioned within the imaging system, typically including aligning the physical center of the scanned portion of the scanned object with the isocenter of the medical imaging device, i.e., "centering".

[0003] In current medical imaging systems, 3D depth cameras are used to assist in automatic positioning of scanned objects. Since the accuracy of body contours acquired by 3D depth cameras is limited, the accuracy of alignment between the scanned object and the isocenter of the medical imaging device needs to be improved. Therefore, there is a need in the art to optimize the current automatic positioning. Summary of the invention

[0004] The purpose of the present invention is to overcome the above and / or other problems in the prior art, and it can optimize the automatic positioning in the medical imaging system and improve the centering accuracy.

[0005] According to a first aspect of the present invention, a method for automatically positioning a scanned object in medical imaging is provided. The method comprises the following steps: obtaining scan information of a scanned object to be imaged to determine a scan feature of the scanned object; identifying a corresponding offset representation value in a mapping table between scan features and offset representation values ​​based on the scan feature of the scanned object; and adjusting a target position of the scanned object in the automatic positioning of the scanned object based on the corresponding offset representation value.

[0006] According to a second aspect of the present invention, a medical imaging system is provided. The system includes a medical imaging device for scanning and imaging a scanned object; a scanning object moving bed for supporting the scanned object and being movable in the horizontal direction and the vertical direction, wherein the horizontal direction includes the lateral direction and the longitudinal direction, wherein during the scanning imaging, the scanning object moving bed moves along the longitudinal direction; a 3D depth camera for acquiring the body contour of the scanned object; an automatic positioning module for automatically positioning the scanned object according to the scanning information of the scanned object and the acquired body contour; and a positioning optimization module, wherein the positioning optimization module is configured to: acquire the scanning information to determine the scanning feature of the scanned object; identify the corresponding offset representation value in the mapping table between the scanning feature and the offset representation value based on the scanning feature of the scanned object; and adjust the target position of the scanned object in the automatic positioning based on the corresponding offset representation value.

[0007] Preferably, the mapping table is established by the following steps: acquiring historical imaging scan data, the historical imaging scan data including historical scanning information and historical offsets associated with multiple scanning processes; determining the scanning features of the scanning object of each scanning process from the historical scanning information of the scanning process, the scanning features of the scanning object including the anatomical structure category of the scanning object; for the same scanning feature, calculating the statistical value of its historical offset to determine the statistical value or the opposite of the statistical value as the offset characterization value corresponding to the scanning feature; and generating a mapping table between different scanning features and their offset characterization values.

[0008] Preferably, the historical scanning information includes a scanning protocol and / or a scanning descriptor, and the anatomical structure category of the scanned object is determined based on the scanning protocol and / or the scanning descriptor.

[0009] Preferably, the scanning characteristics also include the age group, gender and / or body shape of the scanned object, and the historical scanning information includes information for determining the age group, gender and / or body shape of the scanned object.

[0010] Preferably, the historical scanning information further includes a positioning identifier for identifying whether each scanning process adopts manual positioning or automatic positioning, wherein the mapping table is generated only for the scanning process that adopts automatic positioning among the multiple scanning processes.

[0011] Preferably, the scanning feature comprises an anatomical structure category, the scanning information comprises a scanning protocol and / or a scanning descriptor, and the step of determining the scanning feature of the scanned object comprises: determining the anatomical structure category of the scanned object based on the scanning protocol and / or the scanning descriptor.

[0012] Preferably, the scanning feature includes an anatomical structure category, the scanning information includes a scanning range, and the step of determining the scanning feature of the scanned object includes: using a 3D camera to identify multiple landmarks of the scanned object, and determining the anatomical structure category of the scanned object based on a positional relationship between at least one of the multiple landmarks and the scanning range.

[0013] Preferably, the scanning characteristics also include the age group, gender and / or body shape of the scanned object, and the scanning information includes information for determining the age group, gender and / or body shape of the scanned object.

[0014] Preferably, the information used to determine the body shape of the scanned object includes the BMI of the scanned object or the body contour of the scanned object acquired by using a 3D camera.

[0015] Preferably, the age range of the scanned object includes adults and children, and the body types of the scanned object include obese, normal and thin.

[0016] Preferably, the anatomical structure categories include head, chest, abdomen and pelvis, pelvis, lumbar spine and heart.

[0017] Preferably, the method further includes the following steps: using the medical imaging system to scan and image the anatomical structure of the scanned object according to the scanning information to generate an image file, wherein during the scanning imaging, the scanned object moves in a horizontal direction; processing the image file to obtain the center point of the anatomical structure; calculating the current offset in the vertical direction between the center point of the anatomical structure and the isocenter of the medical imaging system; and using the scanning feature of the scanned object and the current offset to adjust the offset characterization value corresponding to the scanning feature of the scanned object in the mapping table.

[0018] Preferably, the adjusting step comprises: performing statistical calculation on the offset characterization value corresponding to the scanning feature of the scanning object and the current offset to determine a new offset characterization value.

[0019] Preferably, the horizontal direction includes a transverse direction and a longitudinal direction, wherein the step of adjusting the target position of the scanning object includes adjusting the target position of the scanning object in the vertical direction or the transverse direction.

[0020] According to a third aspect of the present invention, a processor is provided, which is configured to execute the above method.

[0021] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method described above when the program is executed by a processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention may be better understood by describing exemplary embodiments of the present invention in conjunction with the accompanying drawings, in which:

[0023] Figure 1 An exemplary CT imaging system is shown.

[0024] Figure 2 Shows something like Figure 1 An exemplary imaging system of a CT imaging system.

[0025] Figure 3 is a flow chart of a method for optimizing automatic positioning of a patient according to an exemplary embodiment of the present invention.

[0026] Figure 4 Schematic diagram showing a mapping table between scan features and offset characterization values.

[0027] Figure 5 An example of a mapping table is shown.

[0028] Figure 6 A flowchart showing establishment of a mapping table according to an embodiment of the present invention is shown;

[0029] Figure 7 Screen shot showing an example table of historical imaging scan data acquired during the process of building a mapping table.

[0030] Figure 8 An example of a mapping table between scan features and offset characterization values ​​is shown.

[0031] Fig. 9 Schematic diagram showing the scan field of view (SFOV) of an x-ray fan or cone beam.

[0032] Fig.10 An example image showing a 90° scout scan.

[0033] Fig.11 Schematic diagram showing examples of human body landmarks and the positional relationship between the landmarks and the scanning range.

[0034] Figure 12-16 Various situations of the positional relationship between at least one landmark and the scanning range are respectively shown.

[0035] Fig.17 A flowchart showing adaptive optimization of a mapping table according to an embodiment of the present invention is shown;

[0036] Fig.18 The mapping table generated according to the method described above and the schematic diagram of the adaptive optimization are exemplarily shown.

[0037] Fig.19 An example of an electronic device according to an embodiment of the present invention is shown.

[0038] In the accompanying drawings, similar components and / or features may have the same numerical reference number. In addition, components of the same type may be distinguished by following the reference number with a letter that distinguishes between similar components and / or features. If only the first numerical reference number is used in the specification, the description applies to any similar component and / or feature having the same first numerical reference number, regardless of the letter subscript. DETAILED DESCRIPTION

[0039] The specific embodiments of the present invention will be described below. It should be noted that in the specific description of these embodiments, in order to provide a concise description, it is impossible for this specification to provide a detailed description of all the features of the actual embodiments. It should be understood that in the actual implementation of any embodiment, just as in the process of any engineering project or design project, in order to achieve the specific goals of the developer and to meet system-related or business-related restrictions, various specific decisions are often made, and this will also change from one embodiment to another. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the content disclosed by the present invention, some changes such as design, manufacturing or production based on the technical content disclosed in this disclosure are just conventional technical means, and should not be understood as insufficient content of this disclosure.

[0040] Unless otherwise defined, the technical or scientific terms used in the claims and the specification shall have the usual meanings understood by persons with ordinary skills in the technical field to which the invention belongs. The words "first", "second" and similar words used in the patent application specification and the claims of the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Words such as "one" or "a" do not indicate a quantitative limitation, but indicate the existence of at least one. Words such as "include" or "comprise" mean that the elements or objects appearing before "include" or "comprise" include the elements or objects listed after "include" or "comprise" and their equivalent elements, and do not exclude other elements or objects. Words such as "connect" or "connected" and similar words are not limited to physical or mechanical connections, nor are they limited to direct or indirect connections. "Scanning objects" generally include but are not limited to patients, animals or other objects detected by medical imaging equipment.

[0041] Patient anatomy, position, and orientation can all affect radiographic results. Improper position and / or orientation of the patient during or prior to a scan can significantly affect both image noise and patient radiation dose. As an example, placing the patient in an off-center position can result in imaging artifacts and unnecessary radiation exposure to more sensitive areas of the body.

[0042] The required patient position and orientation (e.g., posture) for radiological examinations are based on the body part to be imaged, the suspected defect or disease, and the patient's condition, wherein the scheme for positioning is determined by the radiologist. The prescribed scheme is then executed by the technician operating the imaging system in order to obtain accurate diagnostic information and reduce the patient's x-ray exposure. In addition, the technician can manually adjust the height and horizontal position of the scanning table on which the patient is positioned in order to align the patient for radiological examination. However, the technician may produce technical errors due to, for example, the high workload and low efficiency of manual positioning. For example, the technical error may cause the image obtained during the radiological examination to have overexposure, underexposure, or wrong positioning of the patient. Therefore, the radiologist may decide to reject and repeat the scan for accurate diagnosis. In such examples, a second radiograph may be requested immediately when the patient is free. Alternatively, the patient may have to return for an additional appointment to rescan. Both options increase patient discomfort, patient exposure to radiation, cognitive stress on the scan operator, and the amount of time until diagnosis.

[0043] Therefore, automatic patient positioning technology has been adopted to speed up the radiology examination workflow. This includes integrating time-of-flight (ToF) or depth cameras into the radiology examination room. Prior to radiological imaging, the ToF or depth camera can be used to generate a 3D depth image of the patient. The 3D depth image can be used to determine the patient's structure, including anatomical key points, body contours, body volume / thickness, and the position / orientation of the patient relative to the workbench. The horizontal scanning range of the patient's structure can then be determined based on the patient's structure and the anatomical structure to be imaged, and the scanning height (i.e., the position in the vertical direction) of the patient's structure can be roughly determined based on whether the anatomical structure to be imaged is the head or the body, and it is desired to center the anatomical structure to be imaged to align with the CT isocenter (ISO center).

[0044] There are currently two methods for patient centering: (1) manually moving the workbench using buttons on the interactive control panel to visually center the patient; and (2) automatic patient positioning based on the body contour captured by a 3D depth camera. Automatic centering is based on the average body contour center of all scout scans (also known as flat film scans).

[0045] However, due to the limited accuracy of the body contour acquired by the 3D depth camera, the centering (especially the vertical centering) of specific anatomical structures (such as the chest, lumbar spine, ankles, musculoskeletal system (MSK), etc.) or special patients (pediatrics, obese patients) is not good enough. For example, when it is desired to image the chest of an obese patient, the automatic centering in the automatic patient positioning is based on the average body contour center of all positioning scan ranges, so even after automatic centering, the chest center of the obese patient deviates greatly from the CT isocenter in the vertical direction. Therefore, despite the use of automatic patient positioning before scanning, discarding the scan and repeating the scan may continue to occur.

[0046] Therefore, according to the embodiments disclosed herein, a method and system for automatically positioning a scanned object in medical imaging is provided. In one embodiment, scanning information of a scanned object to be imaged can be obtained to determine a scanned object scanning feature; a corresponding offset characterization value is identified in a mapping table between the scanned feature and the offset characterization value based on the scanned object scanning feature; and a target position of the scanned object in the automatic positioning of the scanned object is adjusted based on the corresponding offset characterization value.

[0047] Although the operating environment of the present invention is described for an X-ray computed tomography (CT) system, it should be understood that the technical solutions of the present invention are also applicable to other medical imaging systems and / or medical imaging devices that utilize an imaging bore hole and a worktable, such as an x-ray imaging system, a magnetic resonance imaging (MRI) system, a positron emission tomography (PET) imaging system, a single photon emission computed tomography (SPECT) imaging system, and combinations thereof (e.g., multi-modality imaging systems, such as PET / CT, PET / MR imaging systems). The present invention's discussion of the CT imaging modality is provided only as an example of a suitable imaging modality.

[0048] Figure 1 An exemplary CT imaging system 100 is shown. Specifically, the CT imaging system 100 is configured to image a subject 112 (such as a patient, an inanimate object, one or more manufactured parts, industrial parts) and / or a foreign object (such as an implant, a stent, and / or a contrast agent present in the body). Throughout this disclosure, the terms "subject" and "patient" may be used interchangeably, and it should be understood that, at least in some examples, a patient is a type of subject that can be imaged by a CT imaging system, and a subject can include a patient. In one embodiment, the CT imaging system 100 includes a gantry 102, which in turn may also include at least one x-ray radiation source 104, which is configured to project an x-ray radiation beam (or x-rays) 106 (see Figure 2) for imaging a patient. Specifically, the x-ray radiation source 104 is configured to project x-rays 106 toward a detector array 108 positioned on an opposite side of the gantry 102. Figure 1 Only a single x-ray radiation source 104 is depicted, but in certain embodiments, multiple radiation sources may be employed to project multiple x-rays 106 toward multiple detectors to acquire projection data corresponding to the patient at different energy levels.

[0049] In some embodiments, the x-ray radiation source 104 projects an x-ray fan or cone beam 106 that is collimated to lie in the XY plane of a Cartesian coordinate system and is generally referred to as an "imaging plane" or "scanning plane." The x-ray beam 106 passes through a subject 112. The x-ray beam 106 is incident on a detector array 108 after being attenuated by the subject 112. The intensity of the attenuated radiation beam received at the detector array 108 depends on the attenuation of the x-rays 106 by the subject 112. Each detector element of the detector array 108 produces a separate electrical signal that is a measure of the beam intensity at the detector location. Intensity measurements from all detectors are acquired individually to produce a transmission profile.

[0050] In a third generation CT imaging system, a gantry 102 is used to rotate an x-ray radiation source 104 and a detector array 108 around a subject 112 in an imaging plane so that the angle at which the x-ray beam 106 intersects the subject 112 is constantly changing. A full gantry rotation occurs when the gantry 102 completes a full 360 degree rotation. A set of x-ray attenuation measurements (e.g., projection data) from the detector array 108 at one gantry angle is referred to as a "view." Thus, a view is each incremental position of the gantry 102. A "scan" of the subject 112 includes a set of views made at different gantry angles or viewing angles during one rotation of the x-ray radiation source 104 and the detector array 108.

[0051] In an axial scan, the projection data is processed to construct an image corresponding to a two-dimensional slice taken through the subject 112. One method for reconstructing an image from a set of projection data is known in the art as a filtered back projection technique. This method converts attenuation measurements from a scan into an integer called a "CT number" or "Houëtsberg unit" (HU), which is used to control the brightness of a corresponding pixel on, for example, a cathode ray tube display.

[0052] In some examples, the CT imaging system 100 may include a depth camera 114 positioned on or outside the gantry 102. As shown, the depth camera 114 is mounted on a ceiling 116 positioned above the subject 112 and oriented to image the subject 112 when the subject 112 is at least partially outside the gantry 102. The depth camera 114 may include one or more light sensors, including one or more visible light sensors and / or one or more infrared (IR) light sensors. In some embodiments, the one or more IR sensors may include one or more sensors within both the near IR range and the far IR range, thereby achieving thermal imaging. In some embodiments, the depth camera 114 may also include an IR light source. The light sensor may be any 3D depth sensor, such as a time of flight (ToF) sensor, a stereo sensor, or a structured light depth sensor, which is operable to generate a 3D depth image, while in other embodiments, the light sensor may be a two-dimensional (2D) sensor, which is operable to generate a 2D image. In some such embodiments, the 2D light sensor may be used to infer depth based on knowledge of light reflection phenomena to estimate 3D depth. Regardless of whether the optical sensor is a 3D depth sensor or a 2D sensor, the depth camera 114 may be configured to output a signal encoding an image to a suitable interface, which may be configured to receive the signal encoding the image from the depth camera 114. In other examples, the depth camera 114 may also include other components, such as a microphone, to enable reception and analysis of directional and / or non-directional sounds from the observed subject and / or other sources.

[0053] In certain embodiments, the CT imaging system 100 further includes an image processing unit 110 configured to reconstruct an image of the patient's target volume using a suitable reconstruction method, such as an iterative or analytical image reconstruction method. For example, the image processing unit 110 may reconstruct an image of the patient's target volume using an analytical image reconstruction method, such as filtered back projection (FBP). As another example, the image processing unit 110 may reconstruct an image of the patient's target volume using an iterative image reconstruction method, such as adaptive statistical iterative reconstruction (ASIR), conjugate gradient (CG), maximum likelihood expectation maximization (MLEM), model-based iterative reconstruction (MBIR), etc.

[0054] As used herein, the phrase "reconstructing an image" is not intended to exclude embodiments of the invention in which data representing an image is generated rather than a visible image. Thus, as used herein, the term "image" broadly refers to both a visible image and data representing a visible image. However, many embodiments generate (or are configured to generate) at least one visible image.

[0055] The CT imaging system 100 also includes a table 115 on which the subject 112 is positioned for imaging. The table 115 may be motorized so that it can move in the horizontal direction (XZ plane) and the vertical direction (Y). The horizontal direction includes the transverse direction (X direction of the medical imaging system) and the longitudinal direction (Z direction of the medical imaging system). During scanning imaging, the table 111 moves in the longitudinal direction. Therefore, the table 115 may include a motor and a motor controller, as will be described below with respect to Figure 2 The table motor controller moves the table 115 by adjusting the motor so as to properly position the subject in the gantry 102 to acquire projection data corresponding to a target volume of the subject. The table motor controller can adjust the height of the table 115 (e.g., the vertical position relative to the ground on which the table is located) and the horizontal position of the table 115 (e.g., the horizontal position along the lateral direction or the longitudinal direction).

[0056] Figure 2 Shows something like Figure 1 1. An exemplary imaging system 200 of the CT imaging system 100 of FIG. 1 is shown in FIG. 1. In one embodiment, the imaging system 200 includes a detector array 108 (see FIG. Figure 1 ). The detector array 108 also includes a plurality of detector elements 202 that together collect the x-ray beam 106 that passes through the subject 112 (see Figure 1 ) to obtain corresponding projection data. Therefore, in one embodiment, the detector array 108 is manufactured in a multi-slice configuration including multiple rows of units or detector elements 202. In such a configuration, one or more additional rows of detector elements 202 are arranged in a parallel configuration for collecting projection data. In some examples, the individual detectors or detector elements 202 of the detector array 108 may include photon counting detectors that register the interaction of individual photons into one or more energy bins. It should be understood that the methods described herein may also be implemented using energy integrating detectors.

[0057] In some embodiments, the imaging system 200 is configured to traverse different angular positions around the subject 112 to obtain the desired projection data. Thus, the gantry 102 and components mounted thereon can be configured to rotate about the rotation center 206 to obtain, for example, projection data at different energy levels. Alternatively, in embodiments where the projection angle relative to the subject 112 varies over time, the mounted components can be configured to move along a general arc rather than along a section of a circle.

[0058] In one embodiment, the imaging system 200 includes a control mechanism 208 to control the movement of components, such as the rotation of the gantry 102 and the operation of the x-ray radiation source 104. In certain embodiments, the control mechanism 208 also includes an x-ray controller 210 configured to provide power and timing signals to the x-ray radiation source 104. Additionally, the control mechanism 208 includes a gantry motor controller 212 configured to control the rotational speed and / or position of the gantry 102 based on imaging requirements.

[0059] In certain embodiments, the control mechanism 208 also includes a data acquisition system (DAS) 214 that is configured to sample analog data received from the detector elements 202 and convert the analog data into digital signals for subsequent processing. 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 218. For example, the storage device 218 may include a hard 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.

[0060] In addition, 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 operations, such as data acquisition and / or processing. In certain embodiments, the computing device 216 controls system operations based on operator input. The computing device 216 receives operator input, which includes, for example, commands and / or scan parameters, via an operator console 220 operatively coupled to the computing device 216. The operator console 220 may include a keyboard (not shown) or a touch screen to allow an operator to specify commands and / or scan parameters.

[0061] Although Figure 2 Only one operator console 220 is shown, but more than one operator console may be coupled to the imaging system 200, e.g., for inputting or outputting system parameters, requesting exams, and / or viewing images. Additionally, in certain embodiments, the imaging system 200 may be coupled to multiple displays, printers, workstations, and / or the like located locally or remotely, e.g., within an institution or hospital or at an entirely different location, via one or more configurable wired and / or wireless networks, such as the Internet and / or a virtual private network.

[0062] In one embodiment, for example, the imaging system 200 includes or is coupled to a picture archiving and communication system (PACS) 224. In an exemplary embodiment, the PACS 224 is further coupled to a remote system (such as a radiology department information system, a hospital information system) and / or to an internal or external network (not shown) to allow operators at different locations to provide commands and parameters and / or gain access to image data.

[0063] The computing device 216 uses operator-supplied and / or system-defined commands and parameters to operate a table motor controller 226, which in turn controls a table motor 228, which can adjust Figure 1 Specifically, the table motor controller 226 moves the table 115 via the table motor 228 so as to appropriately position the subject 112 in the gantry 102 to acquire projection data corresponding to a target volume of the subject 112. For example, the computing device 216 may send a command to the table motor controller 226, thereby instructing the table motor controller 226 to adjust the vertical position and / or horizontal position of the table 115 via the motor 228.

[0064] As previously described, the DAS 214 samples and digitizes the projection data acquired by the detector elements 202. Subsequently, the image reconstructor 230 uses the sampled and digitized x-ray data to perform high-speed reconstruction. Figure 2 The image reconstructor 230 is shown as a separate entity, but in certain embodiments, the image reconstructor 230 may form part of the computing device 216. Alternatively, the image reconstructor 230 may not be present in the imaging system 200, and instead the computing device 216 may perform one or more functions of the image reconstructor 230. Furthermore, the image reconstructor 230 may be located locally or remotely, and may be operably connected to the imaging system 200 using a wired or wireless network. In particular, one exemplary embodiment may use computing resources in a "cloud" network cluster for the image reconstructor 230.

[0065] In one embodiment, the image reconstructor 230 stores the reconstructed image in the storage device 218. Alternatively, the image reconstructor 230 transmits the reconstructed image to the computing device 216 to generate usable patient information for diagnosis and evaluation. In certain embodiments, the computing device 216 transmits the reconstructed image and / or the patient information to a display 232, which is communicatively coupled to the computing device 216 and / or the image reconstructor 230. In one embodiment, the display 232 allows the operator to evaluate the imaged anatomical structure. The display 232 can also allow the operator to select a volume of interest (VOI) and / or request patient information, for example, via a graphical user interface (GUI), for subsequent scanning or processing.

[0066] As further described herein, the computing device 216 may include computer-readable instructions executable to send commands and / or control parameters to one or more of the DAS 214, the x-ray controller 210, the gantry motor controller 212, and the table motor controller 226 according to an examination imaging protocol, the examination imaging protocol including a clinical task / intent, which is also referred to herein as a clinical intent identifier (CID) for the examination. For example, the CID may inform the goal of the procedure based on clinical indications (e.g., general scanning or lesion detection, anatomical structures of interest, quality parameters, or other goals), and may further define the subject position and orientation (e.g., posture) required during the scan (e.g., supine and feet first). The operator of the system 200 can then position the subject on the table according to the subject position and orientation specified by the imaging protocol. In addition, the computing device 216 can set and / or adjust various scan parameters (e.g., dose, gantry rotation angle, kV, mA, attenuation filter) according to the imaging protocol. For example, the imaging protocol may be selected by an operator from a plurality of imaging protocols stored in a memory on the computing device 216 and / or a remote computing device, or the imaging protocol may be automatically selected by the computing device 216 based on received patient information.

[0067] During the examination / scanning phase, it may be desirable to expose the subject to the lowest possible radiation dose while still maintaining the desired image quality. In addition, reproducible and consistent imaging quality may be desired between examinations and between subjects, as well as between different imaging system operators. Therefore, the imaging system operator may perform manual adjustments to the table position and / or subject position, for example to center the desired patient anatomy in the center of the gantry hole. However, such manual adjustments may be error-prone. Therefore, the CID associated with the selected imaging protocol may be mapped to various subject positioning parameters, including subject posture and orientation, table height, anatomical references for scanning, and start and / or end scan positions.

[0068] Thus, the depth camera 114 may be operably and / or communicatively coupled to the computing device 216 to provide image data to determine the structure of the subject, including posture and orientation. In addition, various methods and processes further described herein for determining the structure of a patient based on image data generated by the depth camera 114 may be stored as executable instructions in a non-transitory memory of the computing device 216.

[0069] In addition, in some examples, the computing device 216 may include a camera image data processor 215 that includes instructions for processing information received from the depth camera 114. The information received from the depth camera 114 (which may include depth information and / or visible light information) may be processed to determine various subject parameters, such as subject identity, subject physique (e.g., height, weight, patient thickness), and current subject position relative to the table and the depth camera 114. For example, prior to imaging, an image reconstructed from point cloud data generated by the camera image data processor 215 based on the image received from the depth camera 114 may be used to estimate the body contour or structure of the subject 112. The computing device 216 may use these subject parameters to, for example, perform patient-scanner contact prediction, scan range overlay, and scan key point calibration, as will be described in more detail herein. In addition, the data from the depth camera 114 may be displayed via the display 232.

[0070] In one embodiment, information from the depth camera 114 can be used by the camera image data processor 215 to perform tracking of one or more subjects in the field of view of the depth camera 114. In some examples, the image information (e.g., depth information) can be used to perform skeletal tracking, where multiple joints of the subject are identified and analyzed to determine the subject's motion, posture, position, etc. The position of the joints during skeletal tracking can be used to determine the above-mentioned subject parameters. In other examples, the image information can be used directly to determine the above-mentioned subject parameters without skeletal tracking.

[0071] Based on these subject positioning parameters, the computing device 216 can output one or more alerts to the operator related to the patient posture / orientation and the prediction of the results of the examination (e.g., scan), thereby reducing the likelihood that the subject will be exposed to a higher than expected radiation dose and improving the quality and reproducibility of the images generated by the scan. As an example, the estimated body structure can be used to determine whether the subject is in the imaging position prescribed by the radiologist, thereby reducing the incidence of repeating the scan due to improper positioning. In addition, the amount of time spent by the imaging system operator to position the subject can be reduced, thereby allowing more scans to be performed in a day and / or allowing additional subject interactions.

[0072] Based on the depth of the camera (such as Figure 1 and Figure 2 The controller (e.g., Figure 2 The computing device 216) can extract patient structure and posture estimates based on images received from the depth camera, thereby enabling different patient orientations to be distinguished from each other.

[0073] The CT imaging system 100 can perform an imaging examination based on a scan protocol. A scan protocol is a description of an imaging examination. The scan protocol can contain a description of the body parts involved, for example, medical terms or colloquial terms for the body parts. The scan protocol can provide various parameters and related information for performing scans and post-processing, such as power values, duration of radiation, movement speed, radiation energy, and time delay between image captures, etc. It is contemplated that any configurable technical parameters that should be used on the imaging system 110 for an imaging examination can be defined in the scan protocol.

[0074] The CT imaging system 100 may have an automatic patient positioning function, that is, the patient may be automatically positioned to the scanning start position in the opening of the gantry 102 based on the examination instruction or the scanning protocol, and may be moved to the scanning end position in the longitudinal direction during scanning imaging. The current automatic patient positioning function may automatically determine the scanning range in the longitudinal direction based on the anatomical structure to be imaged (e.g., from the examination instruction or the scanning protocol) and the patient structure from the depth camera 114, but since the accuracy of the body contour acquired by the depth camera 114 is limited and the automatic positioning is generally for the average body contour center of all positioning scanning ranges, the accuracy of the isocenter alignment between the scanned object and the medical imaging device needs to be improved.

[0075] According to an embodiment of the present invention, a method for automatic positioning of a patient in medical imaging is provided. Figure 3 , Figure 3 FIG. 3 is a flow chart of a method 300 for automatically positioning a patient according to an exemplary embodiment of the present invention. Figure 1 or Figure 2 The imaging systems 100 and 200 shown in FIG. Figure 3 As shown, the method 300 for automatic patient positioning according to the embodiment may include the following steps S310 to S350 .

[0076] In step S310 , scan information of a patient to be imaged is acquired to determine patient scan features.

[0077] The scan information may be part or all of the information derived from the examination instruction or the scan protocol. The examination instruction may come from a radiology information system (RIS), may be selected from a predefined list stored on the medical imaging system 100, or may be input by a user using an input unit (e.g., by keyboard or voice). The examination instruction may include, for example, the patient's age, sex, weight, body part (such as kidney, liver, spleen, stomach, adrenal gland, pancreas, colon, etc.) or body region (such as brain, neck, heart, chest, abdomen, knee, etc.), previous diagnosis, imaging device type, medical institution-specific application of the imaging device, layout planning of the imaging device, and / or contrast agent information. It is contemplated by those skilled in the art that the examination instruction may also include other parameters. The scan protocol may be pre-stored in the medical imaging system 100, for example, in a memory of the computing device 216. The scan protocol may also be stored in a separate memory, or in a remote cloud, in which case the scan protocol may be transmitted to the computing device 216 via a wired or wireless network. The scan protocol may be provided by the manufacturer of the imaging system 110, or may be pre-defined by a user of the medical imaging system 100. The scan protocol may also be provided by a user of a medical imaging system of another medical institution. In an embodiment of the present application, the scan information includes at least information about a body part or body region to be imaged so as to facilitate determining patient scan characteristics. For example, the scan information may include a scan protocol and / or a scan descriptor, and the step of determining the patient scan characteristics may include: determining the anatomical structure category of the patient to be imaged based on the scan protocol and / or the scan descriptor. The scan descriptor may include specific terms extracted from the examination instruction.

[0078] In step S330 , a corresponding offset characterization value is identified in a mapping table between scan characteristics and offset characterization values ​​based on the patient scan characteristics.

[0079] Figure 4 A schematic diagram showing a mapping table between scan features and offset characterization values. For example, when the patient scan feature is determined to be C in step S310, the corresponding offset characterization value (ie, characterization value 3) can be identified from the mapping table based on the scan feature C in step S330.

[0080] In some embodiments of the invention, the scan features may include anatomical structure categories such as head, thorax, abdo-pelvic, pelvis, lumbar spine, and heart. Figure 5 An example of a mapping table is shown. As shown in the figure, different anatomical structure categories and associated characterization values ​​(exemplified in millimeters) are stored in the mapping table. Note that the present invention is not intended to limit the number and characteristics of anatomical structure categories, and those skilled in the art can conceive of combinations of different anatomical structure categories.

[0081] In step S350, the target position of the patient in the automatic patient positioning is adjusted based on the corresponding offset characterization value. For example, the centering in the automatic patient positioning may be based on the average body contour center of the patient estimated by the 3D depth camera, and then the position of the patient in the vertical direction (Y direction of the medical imaging system) and / or the lateral direction (X direction of the medical imaging system) is set by aligning the average body contour center with the isocenter of the CT system. In this way, in step S350, the corresponding offset characterization value can be used to modify the position of the patient in the vertical direction or the lateral direction, thereby compensating for the deviation between the center of the anatomical structure to be imaged and the isocenter of the CT system.

[0082] In some embodiments of the present invention, the mapping table may be established through steps S610-S670, such as Figure 6 shown.

[0083] refer to Figure 6 , in step S610, historical imaging scan data is acquired. The historical imaging scan data may include historical scan information and historical offsets associated with multiple scanning processes. In some preferred embodiments of the present invention, multiple scanning processes may be for the same medical imaging system or the same type of medical imaging system and use the same patient automatic positioning function under substantially the same environmental conditions. Substantially the same environmental conditions may be substantially the same field conditions and substantially the same camera installation positions of the medical imaging system. The same patient automatic positioning function may be patient automatic positioning based on the same algorithm used by the 3D depth camera. The historical scan information may include a scan protocol and / or a scan descriptor, as described above.

[0084] In step S630, the scanning features of the object of each scanning process are determined from the historical scanning information of the scanning process. The scanning features of the object include the anatomical structure category of the object. The anatomical structure category of the object can be determined based on the scanning protocol and / or the scanning descriptor.

[0085] In step S650, for the same scanning feature, the statistical value of its historical offset is calculated to determine the offset characterization value corresponding to the scanning feature. The statistical value of the historical offset may be an average value of multiple historical offsets, but the present invention is not limited thereto, and other statistical values ​​may be conceived, such as a weighted average value, a median value, etc. In some embodiments of the present invention, the statistical value (A) of the historical offset may be determined as the offset characterization value. In other embodiments of the present invention, the opposite number (-A) of the statistical value of the historical offset may be determined as the offset characterization value.

[0086] In step S670, a mapping table between different scanning features and their offset representation values ​​is generated.

[0087] In some embodiments of the present invention, the scan characteristics may also include the age group, gender and / or body type of the subject, and the historical scan information may include information for determining the age group, gender and / or body type of the subject. The information for determining the body type of the patient may include the patient's BMI or the patient's body contour captured using a 3D camera.

[0088] In some embodiments of the present invention, the historical scanning information may further include a positioning identifier for identifying whether each scanning process adopts manual positioning (identifier "1") or automatic positioning (identifier "0"). In this way, a mapping table may be generated only for scanning processes that adopt automatic positioning during multiple scanning processes. The positioning identifier may be extracted from a log file of the patient's automatic positioning.

[0089] Figure 7 A screenshot of an example table of historical imaging scan data acquired during the process of establishing a mapping table is shown. In this example, the historical imaging scan data includes a protocol description for each examination, the purpose of the scan (which can be used as a scan descriptor), the patient orientation (head-first or feet-first), a positioning identifier (1 for manual positioning, 0 for no manual positioning), age group, gender, body type, etc. The historical imaging scan data also includes an offset for each examination (the vertical or lateral deviation between the center of the anatomical structure imaged each time and the isocenter of the CT system).

[0090] In some embodiments of the present invention, a mapping table may be established for multiple scanning features. Figure 7 In the example, you can select anatomical structure category, gender, age group and body type to create a multi-level mapping table. Figure 8 As shown, for six anatomical structure categories (head, chest, abdominal pelvis, pelvis, lumbar spine and heart), gender (male and female), age group (adult and child) and body type (obese O, normal N and thin T), the established mapping table may contain 6*2*2*3=72 mapping entries. The same anatomical structure category, gender, age group and body type correspond to an offset characterization value, and the offset characterization value may be a statistical value (e.g., an average value) of multiple offset values ​​corresponding to multiple scanning processes with the same anatomical structure category, gender, age group and body type in the historical scanning information. In addition, only those scanning processes in the historical scanning information that have not been manually positioned may be selected to calculate the statistical value of the offset. In some cases, the automatic positioning operation of the patient may result in large deviations in the vertical or lateral directions. The operator of the imaging system may choose to correct such deviations through manual adjustment. The offset value data of those scanning processes that include manual adjustment need to be excluded to avoid affecting the objectivity of the statistical value of the offset value data brought about by the automatic positioning of the patient. In some embodiments of the present invention, for the same scanning features (e.g. Figure 8For the same anatomical structure category, gender, age group and body type as shown in , a scanning process greater than a threshold number can be selected to establish a mapping table, and the threshold number can be 10, 20, 30, 40 or more. In this way, a statistical value with an offset optimized for accuracy will be generated.

[0091] In some embodiments of the present invention, the offset in the historical scan information can be obtained by processing the original medical image. In various embodiments, the original medical image data can be stored according to the DICOM standard or data model to obtain a DICOM image. A DICOM file can include a file header part, a file meta information part, and a single service object pair (SOP) instance. The file header part consists of a 128-byte preamble, followed by the characters DICM, all in uppercase. The file header part is followed by the file meta information. This part follows the tagged file format and contains information or metadata about the file, such as the patient to which it belongs (e.g., patient name, patient identification number, patient date of birth, etc.), the study to which it belongs (e.g., study universal identifier (UID), study date, consulting physician, accession number, etc.), the series and study to which it belongs (e.g., series UID, series number, modality type, etc.), etc. This metadata allows querying and indexing of DICOM fields.

[0092] See also Fig. 9 , which shows a schematic diagram of the scanning field of view (SFOV) of the x-ray radiation source 104 projecting a fan or cone beam of x-rays to the detector array 108. The CT system has its own coordinate system. The center of the scanning field of view (SFOV) is the center of the CT system (ISO center). The default coordinate is (0,0,0), which is the ideal positioning center. After the patient is positioned, the offset between the center of the actual scanning part and the isocenter actually represents the error in the Y direction or X direction. Fig.10 An example of error in the Y direction is shown. Along the Z direction perpendicular to the XY plane (i.e., the direction in which the patient enters and exits the gantry opening), the coordinates of each point in the Y direction or X direction are recorded as vectors in the DICOM header. Therefore, the offset of each scanning process can be determined by the following methods: obtain the DICOM original file of each scanning process, read the coordinate vector in the DICOM header; remove the air and bed board parts according to the size of the CT value; starting from the minimum coordinate vector of the scanning part, only extract the coordinate vectors of the middle 30%-70% of the scanning part; average the extracted coordinate vectors to obtain the actual DICOM center value (equivalent to the center of the actual scanning part).

[0093] In some embodiments of the present invention, the DICOM file obtained based on the 90° positioning scan ( Fig.10 An example of a 90° positioning scan image is shown) for the same scan feature (e.g. Figure 8 The offset in the Y direction can be determined based on the same anatomical structure category, gender, age group and body type shown in FIG. Similarly, the offset in the X direction can be determined for the same scan feature based on positioning scans at other angles.

[0094] In some embodiments of the present invention, when the scanning information includes a preset scanning range, the anatomical structure category in the patient's scanning features can also be determined in step S310 in the following manner: using a 3D camera to identify multiple landmarks of the patient, and determining the anatomical structure category of the patient based on the positional relationship between at least one of the multiple landmarks and the scanning range.

[0095] See also Fig.11 , the left side of the figure shows an example of a human body landmark; the right side shows the start position (S) and end position (I) of the scanning range 1100 from the perspective of the 3D camera and one of the landmarks (Landmark N ) and its front and rear landmarks N+1 and Landmark N-1 ) is a schematic diagram of the positional relationship between the landmarks. In this schematic diagram, the scanning range 1100 covers the landmarks. N ) and its front and rear landmarks N+1 and Landmark N-1 ), which can be expressed as S>Landmark N+1 >Landmark N >Landmark N-1 >I.

[0096] Combine the following Figure 12-16 A schematic diagram illustrating the principle of determining the anatomical structure category of a patient by describing the positional relationship between at least one landmark and a scanning range 1100 .

[0097] Fig.12 The scan range 1100 is shown to cover a landmark. N ) (S>Landmark N >I). Assume that the landmark N ) are respectively Fig.11 The six example landmarks shown on the left can be used as reference Fig.12 The corresponding table in the table is used to determine the patient's anatomical structure category. N ) is OM, the patient's anatomical structure category can be determined as the head, so the corresponding offset representation value can be identified in the mapping table between the scan features of the head and the offset representation value for adjustment. N) is SN, the patient's anatomical structure category can be determined as chest, so the corresponding offset representation value can be identified in the mapping table between the scan features of the chest and the offset representation value for adjustment. N ) is XY, the patient's anatomical structure category may be abdomen or heart. In this case, it is necessary to combine other scanning information to make a judgment. For example, the keyword "heart" can be searched from the examination instruction or scanning protocol to determine whether the anatomical structure category is heart. If so, the corresponding offset representation value can be identified in the mapping table between the scanning features containing the heart and the offset representation value to make adjustments. If not, the patient's anatomical structure category may be abdomen. In this case, it can be considered that automatic centering of the body is sufficient for abdominal scanning, so no adjustment is made (represented as "other" in the figure). When the landmark (Landmark N ) is IC, the patient's anatomical structure category may be pelvis or lumbar spine. In this case, it is necessary to combine other scanning information to make a judgment. For example, the keyword "lumbar spine" can be searched from the examination instruction or scanning protocol to determine whether the anatomical structure category is lumbar spine. If it is, the corresponding offset representation value can be identified in the mapping table between the scanning features containing the lumbar spine and the offset representation value for adjustment. If not, the patient's anatomical structure category may be pelvis. In this case, the corresponding offset representation value can be identified in the mapping table between the scanning features containing the pelvis and the offset representation value for adjustment. When the landmark (Landmark N ) is KN or AJ, the patient's anatomical structure category can be determined as a knee or ankle joint.

[0098] Fig.13 Show Landmark N >S>Landmark N-1 >I. Assume that the landmark N ) are respectively Fig.11 The six example landmarks shown on the left can be used as reference Fig.13 The patient's anatomical structure category is determined by the correspondence table in . Fig.13 The anatomical structure category is determined by the details of the parts and Fig.12 They are the same or similar and will not be described in detail here.

[0099] Fig.14 Show S>Landmark N+1 >I>Landmark N Assume that the landmark N ) are respectively Fig.11 The six example landmarks shown on the left can be used as reference Fig.14The patient's anatomical structure category is determined by the correspondence table in . Fig.14 The anatomical structure category is determined by the details of the parts and Fig.12 They are the same or similar and will not be described in detail here.

[0100] Fig.15 Show S>Landmark N >Landmark N-1 >I. Assume that the landmark N ) are respectively Fig.11 The six example landmarks shown on the left can be used as reference Fig.15 The patient's anatomical structure category is determined by the correspondence table in . Fig.15 The anatomical structure category is determined by the details of the parts and Fig.12 They are the same or similar and will not be described in detail here.

[0101] Fig.16 Show S>Landmark N+1 >Landmark N >I. Assume that the landmark N ) are respectively Fig.11 The six example landmarks shown on the left can be used as reference Fig.16 The patient's anatomical structure category is determined by the correspondence table in . Fig.16 The anatomical structure category is determined by the details of the parts and Fig.12 They are the same or similar and will not be described in detail here.

[0102] In some embodiments of the present invention, method 300 may also include adaptive optimization of the mapping table. For example, after each inspection scan imaging of the medical imaging system, the DICOM image using automatic patient positioning without manual positioning may be processed to obtain a new offset, and the corresponding entry in the mapping table may be updated based on the new offset. Alternatively, the adaptive optimization may also be performed in a certain period, such as after several (e.g., 40) inspection scan imaging of the medical imaging system, the 40 DICOM images may be processed to obtain new statistical values ​​of the offsets for different scanning features, and then based on this, the statistical values ​​of the offsets in the mapping table may be corrected to update the mapping table.

[0103] Therefore, reference Fig.17 , the adaptive optimization of the mapping table can be implemented through steps S1710-S1770. In step S1710, the anatomical structure of the patient is scanned and imaged according to the scanning information using the medical imaging system 100 to generate an image file. During the scanning imaging, the patient moves along the longitudinal direction (i.e., the Z direction of the medical imaging system, which is perpendicular to the XY plane). For example, the image file can be a DICOM file.

[0104] In step S1730, the image file is processed to obtain the center point of the anatomical structure. The center point can be obtained by referring to the Fig. 9 and Fig.10 Described in a manner.

[0105] In step S1750, the current offset between the center point of the anatomical structure and the isocenter of the medical imaging system in the vertical direction or the lateral direction is calculated. In some embodiments, the isocenter may have a default coordinate (0,0,0), in which case the Y coordinate or X coordinate of the center point of the anatomical structure represents the offset.

[0106] In step S1770, the offset characterization value corresponding to the patient scan feature in the mapping table is adjusted using the patient scan feature and the current offset. The adjustment may be to perform statistical calculation on the offset characterization value corresponding to the patient scan feature and the current offset to determine a new offset characterization value. In some embodiments, if the offset characterization value is a statistical value of the historical offset, the statistical calculation may be a sum. In other embodiments, if the offset characterization value is the opposite of the statistical value of the historical offset, the statistical calculation may be a difference.

[0107] In some embodiments of the present invention, when the patient scan features include the patient's body shape, the information used to determine the patient's body shape may include the patient's BMI or the patient's body contour collected using a 3D camera. In other words, the information used to determine the patient's body shape may obtain the patient's BMI from a radiology information system (RIS). Alternatively, in the absence of the patient's BMI data, the patient's body contour collected by the 3D depth camera 114 may be used to analyze and evaluate the patient's body shape.

[0108] See also Fig.18, which exemplarily shows a schematic diagram of a mapping table and adaptive optimization generated according to the method described above. In this example, the patient scan features include anatomical structure type (taking six categories as an example), gender (male / female), age group (adult / child) and body type (obese / thin / normal), totaling 72 combinations, so the mapping table has entries representing 72 mapping relationships. During cycle 1, multiple scanning processes are performed, and when the valid data of each combination (the offset using automatic patient positioning without manual intervention) reaches a certain number (for example, 40 times), the offset average value (i.e., offset value 1, offset value 2, ..., offset value 72) can be calculated. In this way, subsequent scans of the imaging system 100 can optimize the centering effect based on the mapping table. Afterwards, after the mapping table is used for optimization for a period of time (i.e., cycle 2), for multiple scanning processes during cycle 2, when the valid data of each combination (the offset using automatic patient positioning without manual intervention) reaches a certain number (e.g., 1 time, 10 times, 20 times, 40 times or more), the average value of the offset that still exists in the automatic patient positioning after optimization using the mapping table (i.e., offset value 1', offset value 2', ..., offset value 72') can be calculated. In this way, the offset average value in the mapping table can be updated by adding the offset value 1, offset value 2, ..., offset value 72 of cycle 1 to the offset value 1', offset value 2', ..., offset value 72' of cycle 2, respectively, thereby realizing adaptive optimization of the mapping table. The adaptive optimization of the mapping table can be performed based on the periodic generation and iteration of the offset average value, thereby continuously improving the optimization of the centering effect of automatic patient positioning using the method of the present application.

[0109] Similar to the above method, the present invention also provides a corresponding medical imaging system.

[0110] Medical imaging systems (e.g. Figure 1 The imaging system 100 or 200 in or 2 may include a medical imaging device for scanning and imaging a patient, a patient moving bed, a 3D depth camera, an automatic positioning module, and a positioning optimization module.

[0111] The patient moving bed (e.g., workbench 115) is used to support the patient and can move in the horizontal direction (including the lateral direction and the longitudinal direction) and the vertical direction. During scanning imaging, the patient moving bed moves in the longitudinal direction (perpendicular to the beam plane). The 3D depth camera (e.g., depth camera 114) is used to collect the body contour of the patient. The automatic positioning module is used to automatically position the patient according to the patient's scanning information and the collected body contour. The positioning optimization module is configured to perform the following operations: obtain scanning information to determine the patient's scanning characteristics; identify the corresponding offset characterization value in the mapping table between the scanning characteristics and the offset characterization value based on the patient's scanning characteristics; and adjust the target position of the patient in the automatic positioning based on the corresponding offset characterization value. The medical imaging device can be configured to scan and image the patient's anatomical structure according to the scanning information to generate an image file. The medical imaging system can also include an adjustment module, which is configured to: process the image file to obtain the center point of the anatomical structure; calculate the current offset between the center point of the anatomical structure and the isocenter of the medical imaging system in the vertical direction or the lateral direction; and adjust the offset characterization value corresponding to the patient's scanning characteristics in the mapping table using the patient's scanning characteristics and the current offset. The details of the operations of the positioning optimization module and the adjustment module are the same or similar to the method 300 described above and are not described again here.

[0112] One or more of the techniques and / or embodiments described above may be implemented in hardware and / or software or include hardware and / or software, for example, modules or devices executed on one or more computing devices 216. Of course, the modules or devices described herein illustrate various functions and are not limited to the structure and function of any embodiment. Instead, the functions of each module or device may be divided and performed differently by more or fewer modules or devices according to various design considerations.

[0113] Exemplary Computing Devices

[0114] Fig.19 An example of an electronic device 1900 according to an embodiment of the present invention is shown. The electronic device 1900 includes: one or more processors 1920; a storage device 1910, which is used to store one or more programs. When the one or more programs are executed by the one or more processors 1920, the one or more processors 1920 implement the method for optimizing the automatic positioning of a patient provided by an embodiment of the present invention. The processor is, for example, a digital signal processor (DSP), a microcontroller, an application specific integrated circuit (ASIC), or a microprocessor.

[0115] Fig.19 The electronic device 1900 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0116] like Fig.19 As shown, the electronic device 1900 is in the form of a general-purpose computing device. The components of the electronic device 1900 may include, but are not limited to: one or more processors 1920, a storage device 1910, and a bus 1950 connecting different system components (including the storage device 1910 and the processor 1920).

[0117] Bus 1950 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0118] The electronic device 1900 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 1900, including volatile and non-volatile media, removable and non-removable media.

[0119] The storage device 1910 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 1911 and / or cache memory 1912. The electronic device 1900 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 1913 may be used to read and write non-removable, non-volatile magnetic media ( Fig.19 not shown, usually called a "hard drive"). Although Fig.19 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 1950 via one or more data medium interfaces. Storage device 1910 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of various embodiments of the present invention.

[0120] A program / utility 1914 having a set (at least one) of program modules 1915 may be stored, for example, in a storage device 1910, such program modules 1915 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may include an implementation of a network environment. The program modules 1915 generally perform the functions and / or methods of any embodiment described herein.

[0121] The electronic device 1900 may also communicate with one or more external devices 1960 (e.g., keyboard, pointing device, display 1970, etc.), one or more devices that enable a user to interact with the electronic device 1900, and / or any device that enables the electronic device 1900 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 1930. Furthermore, the electronic device 1900 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 1940. Fig.19 As shown, the network adapter 1940 communicates with other modules of the electronic device 1900 via the bus 1950. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 1900, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0122] The processor 1920 executes various functional applications and data processing by running the programs stored in the storage device 1910, such as implementing a video processing method provided by an embodiment of the present invention.

[0123] The technology described herein can be implemented in hardware, software, firmware, or any combination thereof, unless specifically described as being implemented in a particular manner. Any features described as modules or components can also be implemented together in an integrated logic device, or separately implemented as discrete but interoperable logic devices. If implemented in software, the technology can be implemented at least in part by a non-transient processor-readable storage medium including instructions, and when the instructions are executed, one or more of the above methods are executed. The non-transient processor-readable data storage medium can form a part of a computer program product that may include packaging materials. The program code can be implemented in a high-level procedural programming language or an object-oriented programming language to communicate with a processing system. If necessary, the program code can also be implemented in assembly language or machine language. In fact, the mechanism described herein is not limited to the scope of any particular programming language. In any case, the language can be a compiled language or an interpreted language.

[0124] One or more aspects of at least some embodiments may be implemented by representative instructions stored on a machine-readable medium that represent various logic within a processor, which when read by a machine causes the machine to fabricate logic for performing the techniques described herein.

[0125] Such machine-readable storage media may include, but are not limited to, a non-transitory tangible arrangement of articles manufactured or formed by a machine or apparatus, including storage media such as: a hard disk; any other type of disk, including floppy disks, optical disks, compact disk-read only memory (CD-ROM), compact disk-rewritable (CD-RW), and magneto-optical disks; semiconductor devices, such as read-only memory (ROM), random access memory (RAM) such as dynamic random access memory (DRAM) and static random access memory (SRAM), erasable programmable read-only memory (EPROM), flash memory, electrically erasable programmable read-only memory (EEPROM); phase change memory (PCM); magnetic or optical cards; or any other type of medium suitable for storing electronic instructions.

[0126] Instructions may also be further sent or received via a communication network using a transmission medium via a network interface device that utilizes any of a number of transmission protocols (e.g., Frame Relay, Internet Protocol (IP), Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Hypertext Transfer Protocol (HTTP), etc.).

[0127] Example communication networks may include a local area network (LAN), a wide area network (WAN), a packet data network (e.g., the Internet), a mobile phone network (e.g., a cellular network), a plain old telephone (POTS) network, and a wireless data network (e.g., a wireless network known as Wi-Fi). The Institute of Electrical and Electronics Engineers (IEEE) 802.11 series of standards, known as ), IEEE 802.15.4 series of standards, peer-to-peer (P2P) networks, etc. In an example, the network interface device may include one or more physical jacks (e.g., Ethernet, coaxial, or telephone jacks) or one or more antennas for connecting to a communication network. In an example, the network interface device may include multiple antennas that communicate wirelessly using at least one of single-input multiple-output (SIMO), multiple-input multiple-output (MIMO), or multiple-input single-output (MISO) technologies.

[0128] The term "transmission medium" shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and includes digital or analog communications signals or other intangible medium for facilitating communication of such software.

[0129] So far, a method for optimizing automatic positioning of a patient in a medical imaging system and a medical imaging system according to the present invention are described, and a processor and a computer-readable storage medium capable of implementing the method are also introduced.

[0130] Through the present invention, the existing automatic patient positioning based on 3D depth cameras in medical imaging systems can be optimized, the centering accuracy can be improved, and thus the imaging quality can be improved. With the present invention, the medical imaging system can reduce the possibility of re-positioning scanning, readjust the height of the workbench, and help optimize the dose, so it has better workflow efficiency and productivity, better user experience and ease of use. Through this improved centering effect, the medical imaging system is more friendly to pediatric hospitals, because the automatic positioning of pediatric patients is not available or has poor effects in the prior art. The present invention is suitable for different field conditions, different camera installation positions, and different user habits, and has flexible applicability. In addition, the technology of the present invention can be implemented as a fully automated process, which is fast and intelligent without the need for manpower or perceptual judgment.

[0131] Some exemplary embodiments have been described above. However, it should be understood that various modifications may be made to the exemplary embodiments described above without departing from the spirit and scope of the present invention. For example, if the described techniques are performed in a different order and / or if the components in the described systems, architectures, devices, or circuits are combined in different ways and / or replaced or supplemented by other components or their equivalents, suitable results may be achieved, and accordingly, these modified other implementations also fall within the scope of protection of the claims.

Claims

1. A method for automatically positioning a scanned object in medical imaging, comprising the following steps: Acquire scanning information of a scanned object to be imaged to determine scanning features of the scanned object; Identifying a corresponding offset characterization value in a mapping table between scan features and offset characterization values ​​based on the scan features of the scanned object; and Based on the corresponding offset characterization value, a target position of the scan object in the automatic positioning of the scan object is adjusted.

2. The method according to claim 1, characterized in that The mapping table is established by the following steps: Acquire historical imaging scan data, wherein the historical imaging scan data includes historical scan information and historical offsets associated with a plurality of scanning processes; Determine a scan feature of a scan object of each scan process from historical scan information of the scan process, wherein the scan feature of the scan object includes an anatomical structure category of the scan object; For the same scanning feature, calculating a statistical value of its historical offset to determine the statistical value or the opposite of the statistical value as an offset characterization value corresponding to the scanning feature; and Generate a mapping table between different scan features and their offset representation values.

3. The method according to claim 2, characterized in that The historical scanning information includes a scanning protocol and / or a scanning descriptor, and the anatomical structure category of the scan object is determined based on the scanning protocol and / or the scanning descriptor.

4. The method according to claim 2, characterized in that The scan characteristics also include the age group, gender and / or body type of the scan object, and the historical scan information includes information used to determine the age group, gender and / or body type of the scan object.

5. The method according to claim 2, characterized in that The historical scanning information further includes a positioning identifier for identifying whether each scanning process adopts manual positioning or automatic positioning, wherein the mapping table is generated only for the scanning process that adopts automatic positioning among the multiple scanning processes.

6. The method according to claim 1, characterized in that The scanning feature comprises an anatomical structure category, the scanning information comprises a scanning protocol and / or a scanning descriptor, and the step of determining the scanning feature of the scan object comprises: determining the anatomical structure category of the scan object based on the scanning protocol and / or the scanning descriptor.

7. The method according to claim 1, characterized in that The scanning feature includes an anatomical structure category, the scanning information includes a scanning range, and the step of determining the scanning feature of the scanned object includes: using a 3D camera to identify multiple landmarks of the scanned object, and determining the anatomical structure category of the scanned object based on a positional relationship between at least one of the multiple landmarks and the scanning range.

8. The method according to claim 6 or 7, characterized in that The scan characteristics further include the age group, gender and / or body type of the scan object, and the scan information includes information for determining the age group, gender and / or body type of the scan object.

9. The method according to claim 8, characterized in that The information used to determine the body shape of the scanned object includes the BMI of the scanned object or the body contour of the scanned object acquired using a 3D camera.

10. The method according to claim 8, characterized in that The age groups of the scanned objects include adults and children, and the body types of the scanned objects include obese, normal and thin.

11. The method according to claim 2 or 6, characterized in that: The anatomical structure categories include head, thorax, abdominal pelvis, pelvis, lumbar spine, and heart.

12. The method according to claim 1, characterized in that The method further comprises the following steps: Using the medical imaging system to scan and image the anatomical structure of the scanned object according to the scan information to generate an image file, wherein during the scanning and imaging, the scanned object moves in a horizontal direction; Processing the image file to obtain a center point of the anatomical structure; Calculating a current offset in a vertical direction between a center point of the anatomical structure and an isocenter of the medical imaging system; and The offset characterization value corresponding to the scanning feature of the scanning object in the mapping table is adjusted using the scanning feature of the scanning object and the current offset.

13. The method according to claim 12, characterized in that The adjusting step includes: performing statistical calculation on the offset characterization value corresponding to the scanning feature of the scanning object and the current offset to determine a new offset characterization value.

14. The method according to claim 1, wherein: The scanning object to be imaged can be moved by a scanning object moving bed in a horizontal direction and a vertical direction, the horizontal direction includes a transverse direction and a longitudinal direction, wherein the step of adjusting the target position of the scanning object includes adjusting the target position of the scanning object in the vertical direction or the transverse direction.

15. A medical imaging system comprising: A medical imaging device, used for scanning and imaging a scanned object; a scanning object moving bed, used for supporting the scanning object and movable in a horizontal direction and a vertical direction, wherein the horizontal direction includes a transverse direction and a longitudinal direction, wherein during the scanning imaging, the scanning object moving bed moves along the longitudinal direction; A 3D depth camera, used to capture the body contour of the scanned object; an automatic positioning module, configured to automatically position the scanned object according to the scanned information of the scanned object and the acquired body contour; and A positioning optimization module, wherein the positioning optimization module is configured to: Acquire the scanning information to determine scanning features of the scanned object; Identifying a corresponding offset characterization value in a mapping table between scan features and offset characterization values ​​based on the scan features of the scanned object; and Based on the corresponding offset characterization value, a target position of the scan object in the automatic positioning is adjusted.

16. The medical imaging system of claim 15, wherein: The mapping table is established by the following steps: Acquire historical imaging scan data, wherein the historical imaging scan data includes historical scan information and historical offsets associated with a plurality of scanning processes; Determine a scan feature of a scan object of each scan process from historical scan information of the scan process, wherein the scan feature of the scan object includes an anatomical structure category of the scan object; For the same scanning feature, a statistical value of its historical offset is calculated to determine the statistical value or the opposite of the statistical value as the offset characterization value corresponding to the scanning feature; and Generate a mapping table between different scan features and their offset representation values.

17. The medical imaging system of claim 16, wherein: The historical scanning information further includes a positioning identifier for identifying whether each scanning process adopts manual positioning or automatic positioning, wherein the mapping table is generated only for the scanning process that adopts automatic positioning among the multiple scanning processes.

18. The medical imaging system of claim 15, wherein: The medical imaging device is configured to scan and image the anatomical structure of the scanned object according to the scan information to generate an image file, and the medical imaging system further includes an adjustment module, which is configured to: Processing the image file to obtain a center point of the anatomical structure; Calculating a current offset in a vertical direction between a center point of the anatomical structure and an isocenter of the medical imaging system; as well as The offset characterization value corresponding to the scanning feature of the scanning object in the mapping table is adjusted using the scanning feature of the scanning object and the current offset.

19. The medical imaging system of claim 15, wherein: The operation of adjusting the target position of the scanning object includes adjusting the target position of the scanning object in the vertical direction or the horizontal direction.

20. A processor for performing the method of any one of claims 1 to 14.

21. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the steps of the method according to any one of claims 1 to 14 are implemented.

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