Method for generating CT image and image data reconstruction apparatus

Abstract

A method of generating a CT image and an image data reconstruction apparatus are provided. The method comprises the steps of obtaining projection measurement data of a CT device scanning an inspection object; an initial scanning image is reconstructed based on the projection measurement data, the initial scanning image comprises a plurality of slice images, and at least one of the slice images comprises a main area image in the scanning view field of the CT equipment and a truncation area image outside the scanning view field of the CT equipment; determining whether a specific type of substance exists in the plurality of slice images; in response to determining that the substance is present in the truncated region image of the plurality of slice images, artifact removal reconstruction is performed on at least one slice image of the plurality of slice images, the artifact removal reconstruction being used to remove artifacts in the plurality of slice images caused by the substance.

Description

Technical Field

[0001] The present disclosure relates to non-invasive diagnostic imaging, and more particularly, to a method of generating CT images and an image data reconstruction apparatus. Background Art

[0002] CT (Computed Tomography) systems are widely used in various medical institutions to perform three-dimensional imaging of a subject's area of ​​interest, such as the lungs, to help clinicians make accurate medical diagnoses of the subject.

[0003] During the CT scan, a detector is used to collect data of X-rays after they pass through the patient's body, and then these collected X-ray data are processed to obtain projection data. These projection data can be used to reconstruct slice images. Complete projection data can reconstruct accurate slice images for diagnosis.

[0004] As image data is reconstructed based on projection measurement data, artifacts (especially metal artifacts) frequently occur. Artifacts are usually caused by implants (such as steel pins, stents, metal fillings, etc.) in the body of the patient being examined. On the image, artifacts can appear as streaks in the slice image, thereby affecting the readability of the reconstructed image.

[0005] In order to reduce artifacts in image representation, special image reconstruction can be performed to remove artifacts, i.e., artifact removal reconstruction. In the past, artifact removal reconstruction was initiated based on slice images of diagnostic scans. However, conventional diagnostic scan images only reconstruct images of the main area within the scanning field of view of the CT device, and images of truncated areas outside the scanning field of the CT device are not reconstructed. When an object causing artifacts exists in the truncated area, it is difficult to initiate artifact removal reconstruction based on the main area image. Summary of the invention

[0006] An object of the present invention is to overcome the above and / or other problems in the prior art, and to enable artifact removal reconstruction correctly when there are objects causing artifacts in the truncation region.

[0007] According to a first aspect of the present invention, a method for generating a CT image is provided, comprising: acquiring projection measurement data of an object scanned by a CT device; reconstructing an initial scan image based on the projection measurement data, wherein the initial scan image comprises a plurality of slice images, and at least one of the plurality of slice images comprises a main region image within a scanning field of view of the CT device and a truncated region image outside the scanning field of view of the CT device; determining whether a specific type of substance exists in the plurality of slice images; in response to determining that substance exists in the truncated region images of the plurality of slice images, performing artifact removal reconstruction on at least one slice image of the plurality of slice images, the artifact removal reconstruction being used to remove artifacts in the plurality of slice images caused by the substance.

[0008] In one embodiment, performing artifact removal reconstruction on at least one slice image among multiple slice images may include: determining an artifact-affected sub-region in the slice image, wherein each of the artifact-affected sub-regions indicates the presence of at least one of the substances; performing artifact removal on the artifact-affected sub-region to obtain an artifact-reduced sub-image; and combining at least a portion of the at least one slice image with the artifact-reduced sub-image.

[0009] In one embodiment, the method may further include: acquiring at least one scouting image of the inspection object at at least one flat scanning angle; and determining an inspection area of ​​the inspection object based on the at least one scouting image.

[0010] In one embodiment, the scout image may be obtained by performing planar projection measurement on the object at one of at least one flat scanning angle, and the projection measurement data may be obtained by performing circumferential projection measurement on the inspection area of ​​the inspection object along the axial direction of the diagnostic scan.

[0011] In one embodiment, it may also include: determining whether there is a substance located within the inspection area or within a threshold range from the inspection area in at least one scout image; and in response to determining that there is a substance located within the inspection area or within a threshold range from the inspection area in at least one scout image, performing artifact removal reconstruction on at least one slice image of the multiple slice images.

[0012] In one embodiment, combining at least a portion of at least one slice image with the artifact-reduced sub-image may include: combining at least one sub-image of an artifact-free shadow region in the at least one slice image with the artifact-reduced sub-image.

[0013] In one embodiment, the sub-region affected by the artifact may include a sub-region where the substance is located and a sub-region near the substance.

[0014] In one embodiment, the substance may include a metallic substance.

[0015] In one embodiment, the sub-region near the substance may be further determined based on one or more of: the location of the substance; the type of the substance; the size of the substance; and the shape of the substance.

[0016] In one embodiment, deep learning may be used to determine whether a substance exists in each of a plurality of slice images.

[0017] According to a second aspect of the present invention, there is provided an image data reconstruction device, comprising: a data acquisition unit, configured to acquire projection measurement data of an object scanned and inspected by a CT device; a reconstruction unit, configured to reconstruct an original scanned image based on the projection measurement data, wherein the original scanned image comprises a plurality of slice images, at least one of the plurality of slice images comprises a main area image within a scanning field of view of the CT device and a truncated area image outside the scanning field of view of the CT device; and a correction unit, configured to perform artifact removal and reconstruction on the original scanned image, the correction unit comprising: a detection unit, configured to determine whether a specific type of substance exists in the plurality of slice images; and an artifact removal and reconstruction unit, configured to perform artifact removal and reconstruction on at least one slice image of the plurality of slice images in response to determining that substance exists in a truncated area image of the plurality of slice images, the artifact removal and reconstruction being used to remove artifacts in the plurality of slice images caused by the substance.

[0018] In one embodiment, the artifact removal and reconstruction unit can be configured to: determine an artifact-affected sub-region in a slice image based at least on the position of the substance, wherein each of the artifact-affected sub-regions indicates the presence of at least one of the substances; perform artifact removal and reconstruction on the artifact-affected sub-region based at least on the position of the substance to obtain an artifact-reduced sub-image; and combine at least a portion of at least one slice image with the artifact-reduced sub-image.

[0019] In one embodiment, the data acquisition unit may be further configured to acquire at least one scout image of the inspection object at at least one flat scanning angle.

[0020] In one embodiment, the scout image may be obtained by performing planar projection measurement on the object at one of at least one flat scanning angle, and the projection measurement data may be obtained by performing circumferential projection measurement on the inspection area of ​​the inspection object along the axial direction of the diagnostic scan.

[0021] In one embodiment, the detection unit may be further configured to: determine whether there is matter in the inspection area or within a threshold range of the inspection area in at least one scout image, and the artifact removal and reconstruction unit may be further configured to: perform artifact removal and reconstruction on at least one slice image among the multiple slice images in response to determining that there is matter in the inspection area or within a threshold range of the inspection area in at least one scout image.

[0022] In one embodiment, the artifact removal and reconstruction unit may be further configured to: combine a sub-image of at least one artifact-free shadow region in at least one slice image with a sub-image with reduced artifacts.

[0023] In one embodiment, the sub-region affected by the artifact may include a sub-region where the substance is located and a sub-region near the substance.

[0024] In one embodiment, the substance may include a metallic substance.

[0025] In one embodiment, the sub-region near the substance may be further determined based on one or more of: the location of the substance; the type of the substance; the size of the substance; and the shape of the substance.

[0026] In one embodiment, the detection unit may be configured to determine whether a substance exists in each of the plurality of slice images by deep learning.

[0027] According to a third aspect of the present invention, there is provided a computer tomography system, comprising: a scanner unit configured to acquire projection measurement data of a detection object; a control device configured to control the scanner unit; and the above-mentioned image data reconstruction device.

[0028] According to a fourth aspect of the present invention, there is provided a non-transitory machine-readable medium comprising a plurality of instructions, which when executed by a processor cause the processor to execute the above method. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present invention may be better understood by describing exemplary embodiments of the present invention in conjunction with the accompanying drawings, in which:

[0030] Figure 1 A schematic diagram of an example CT imaging system 100 is shown;

[0031] Figure 2 Shows something like Figure 1 A block diagram of an exemplary imaging system 200 of the CT imaging system 100;

[0032] FIG3(A) shows a scout image obtained from directly above the subject 112;

[0033] FIG3(B) shows a scout image obtained from the side of the subject 112;

[0034] FIG4(A) illustrates a reconstructed uncorrected scan image;

[0035] FIG4(B) illustrates an image after artifact removal and reconstruction;

[0036] Figure 5A flow chart illustrating an example process 500 for generating a CT image according to the techniques of this disclosure;

[0037] 6(A) and 6(B) illustrate schematic diagrams of a scanning field of view of a CT imaging system 100;

[0038] Figure 7 FIG. 1 shows an example slice image in an initial scan image according to the technology of the present disclosure;

[0039] Figure 8 The figure shows a comparison of slice images before and after artifact removal and reconstruction according to the technology disclosed in the present invention, wherein the left side is a slice image of an initial scan image without enabling artifact removal and reconstruction, and the right side is a corresponding slice image after enabling artifact removal and reconstruction;

[0040] Fig. 9 FIGURES A flow chart illustrating an example process 900 for performing artifact removal reconstruction on a slice image in accordance with the techniques of the present disclosure;

[0041] Fig.10 FIGURES a flow chart illustrating another example process 1000 for generating a CT image according to the techniques of the present disclosure;

[0042] Fig.11 illustrates a block diagram of an example image data reconstruction apparatus 300 in accordance with the techniques of this disclosure; and

[0043] Fig.12 An example block diagram of a computing device 1200 is shown in accordance with the techniques of this disclosure.

[0044] 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

[0045] 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.

[0046] References in the specification to "one embodiment," "an embodiment," "an example embodiment," etc. indicate that the described embodiment may include a particular feature, structure, or characteristic, but not every embodiment may include the particular feature, structure, or characteristic. Furthermore, such phrases do not necessarily refer to the same embodiment. Furthermore, when a particular feature, structure, or characteristic is described in conjunction with an embodiment, it is considered to be within the knowledge of those skilled in the art to affect such feature, structure, or characteristic in conjunction with other embodiments, whether or not explicitly described.

[0047] For purposes of this disclosure, the phrase "A and / or B" means (A), (B), or (A and B). For purposes of this disclosure, the phrase "A, B, and / or C" means (A), (B), (C), (A and B), (A and C), (B and C), or (A, B, and C).

[0048] Unless otherwise defined, the technical or scientific terms used in the claims and the specification shall have the common meanings understood by persons with ordinary skills in the technical field to which the invention belongs. "Include" or "comprising" and similar words mean that the elements or objects appearing before "include" or "comprising" include the elements or objects listed after "include" or "comprising" and their equivalent elements, and do not exclude other elements or objects.

[0049] The following will take the example of Figures 1 to 12Embodiments of the present disclosure are described, wherein the following description relates to various examples of imaging systems. Specifically, methods for generating CT images, image data reconstruction devices, and computer tomography systems are provided. Specific types of materials that cause artifacts as mentioned herein may include any metal objects, non-metal objects, inspection table seams or gaps, components, imaging accessories, etc. that make images unclear or blurred. I. Overview of Imaging System

[0050] Although a CT system is described by way of example, it should be understood that the techniques of the present disclosure may also be useful when applied to images acquired using other imaging modalities, such as x-ray imaging systems, magnetic resonance imaging (MRI) systems, positron emission tomography (PET) imaging systems, single photon emission computed tomography (SPECT) 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 a CT imaging system is provided merely as an example of a suitable imaging system.

[0051] Figure 1 An exemplary CT imaging system 100 is shown. Specifically, the CT imaging system (also referred to as a CT device) 100 is configured to image a subject 112 (such as a patient, an inanimate object, one or more manufactured parts, industrial parts, a foreign object, etc.). Throughout this disclosure, the terms "subject" and "examination object" may be used interchangeably, and it should be understood that, at least in some embodiments, a patient is a type of subject that can be imaged by the CT imaging system 100, and the subject may include a patient. In some embodiments, the CT imaging system 100 includes a gantry 102, which may include at least one x-ray radiation source 104, which is configured to project an x-ray beam (or x-rays) 106 (see Figure 2 ) for imaging a subject 112. 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 some embodiments, multiple x-ray radiation sources 104 may be employed to project multiple x-rays 106 toward multiple detectors to acquire projection data corresponding to the subject 112 at different energy levels.

[0052] In some embodiments, the x-ray radiation source 104 projects a fan-shaped or cone-shaped x-ray 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.

[0053] 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.

[0054] 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.

[0055] In some examples, the CT imaging system 100 may include a depth camera 114 positioned on or external to the gantry 102. Figure 1As shown, the depth camera 114 is mounted on a ceiling 116 positioned above the subject 112 and oriented to image the subject when the subject 112 is at least partially outside the rack 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 in 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 can be used to infer depth based on an understanding 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.

[0056] In some 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.

[0057] 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.

[0058] 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 the vertical position and / or lateral position of the table can be adjusted. Thus, 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 lateral position of the table 115 (e.g., the horizontal position of the table along an axis parallel to the axis of rotation of the gantry 102).

[0059] 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 some embodiments, the imaging system 200 includes a detector array 108 (see FIG. 1). 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 some embodiments, 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 interactions 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.

[0060] In some embodiments, the imaging system 200 is configured to traverse different angular positions around the subject 112 to obtain the desired projection measurement data. Therefore, the gantry 102 and the components mounted thereon can be configured to rotate about the rotation center 206 to obtain, for example, projection measurement data at different energy levels. Alternatively, in embodiments where the projection angle relative to the subject 112 changes over time, the mounted components can be configured to move along a general arc rather than along a section of a circle.

[0061] In some embodiments, the imaging system 200 includes a control mechanism 208 to control movement of components, such as rotation of the gantry 102 and operation of the x-ray radiation source 104. In some 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.

[0062] In some 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.

[0063] 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 some 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.

[0064] 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 some 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.

[0065] In some embodiments, 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.

[0066] The computing device 216 uses operator-supplied and / or system-defined commands and parameters to operate the table motor controller 226, which in turn controls the table motors to adjust Figure 1 102. Specifically, the table motor controller 226 moves the table 115 via the table motor 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 lateral position of the table 115 via the motor.

[0067] As described above, 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 some 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. In addition, 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.

[0068] In some embodiments, 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 subject information (also referred to as examination object information) for diagnosis and evaluation. In some embodiments, the computing device 216 transmits the reconstructed image and / or the subject information to a display 232, which is communicatively coupled to the computing device 216 and / or the image reconstructor 230. In some embodiments, the display 232 allows an 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 subject information, for example, via a graphical user interface (GUI), for subsequent scanning or processing.

[0069] 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 scanning 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 subject information.

[0070] 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.

[0071] 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.

[0072] 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.

[0073] In some embodiments, 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, in which 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.

[0074] 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.

[0075] Based on the depth of the camera (such as Figure 1 and Figure 2 The controller (e.g., Figure 2 The computing device 216 of the present invention may extract patient structure and posture estimates based on images received from the depth camera 114, thereby enabling different patient orientations to be distinguished from each other.

[0076] 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.

[0077] 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 along the z-axis direction during scanning imaging. The current automatic patient positioning function may automatically determine the scanning range in the horizontal 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 its automatic centering can only be roughly aimed at the head or body and the average body contour center of all scout scans (hereinafter also referred to as reconnaissance scans), so the centering accuracy for specific anatomical structures and special patients is not good enough. II. Reconnaissance and Diagnostic Scans

[0078] During the scanning process of the CT imaging system 100, the subject 112 is appropriately positioned in the gantry 102, and the computing device 216 controls the rotation of the gantry 102 through the gantry motor controller 212, so that the x-ray radiation source 104 and the corresponding detector array 108 move along a circle or arc around the subject 112 and simultaneously collect projection data. The computing device 216 can also control the table 115 to move along the axial direction (also called the axial direction of the diagnostic scan, i.e., the axial direction of the diagnostic scan) through the table motor controller 226. Figure 1The table 115 moves along the z-axis direction in the image to obtain projection data of the three-dimensional target volume (also called the examination area) of the subject 112. This process is called "diagnostic scanning". As the subject 112 moves along the workbench 115, multiple sets of projection data can be acquired at certain time intervals to reconstruct multiple slice images. Each slice image corresponds to a set of projection data, representing an image of a certain cross section along the axial direction in the examination area. This set of slice images can be used for diagnosis.

[0079] Since the radiation dose of the diagnostic scan to the subject 112 is relatively large, it is sometimes desired to accurately determine the inspection area before starting the diagnostic scan to reduce unnecessary radiation dose. To this end, a scout scan (also called a plain scan or positioning scan) can be optionally performed before the diagnostic scan. The scout scan takes a single shot of the subject 112 at at least one plain scan angle while the subject 112 remains stationary. The plain scan angle indicates the position of the x-ray radiation source 104 and the corresponding detector array 108 in the circumferential direction of the subject 112.

[0080] Unlike a diagnostic scan that requires the acquisition of projection data of multiple cross-sections along the axial direction of the three-dimensional examination area of ​​the subject 112, a reconnaissance scan only needs to acquire static projection data at one plain scan angle, and the radiation dose generated is very small. FIG. 3(A) shows a reconnaissance image obtained from directly above the subject 112, and FIG. 3(B) shows a reconnaissance image obtained from the side of the subject 112. Using the reconnaissance image, the operator can further determine the examination area to be photographed for the diagnostic scan. Specifically, a reconnaissance image of the area of ​​interest (such as the lungs) can be obtained first, and then the examination area where the diagnostic scan needs to be performed can be determined therefrom. For example, the operator can mark the examination area for the diagnostic scan based on the reconnaissance image in the axial direction of the diagnostic scan ( Figure 1 The boundary on the z-axis in . III. Artifact Removal

[0081] There may be certain types of substances inside or outside the subject 112 that cause artifacts in the image. Such substances may include any metal objects, non-metal objects, seams or gaps of the inspection table, components, imaging accessories, etc. that make the image unclear or blurred. For example, the presence of metal implants will affect the reconstructed scanned image. A typical situation is that the presence of metal objects causes the reconstructed image to produce a large number of black and bright radial stripe artifacts around the metal, which will seriously affect the doctor's judgment of the examination results when the metal objects are relatively large. FIG4(A) illustrates the reconstructed uncorrected scan image.

[0082] The main reasons for the artifacts are as follows: when a specific type of material (for example, a material with a high density) is implanted inside the subject 112, because its attenuation coefficient is much greater than the attenuation coefficient of other parts inside the subject 112, when the rays pass through the material, they will be greatly weakened, resulting in a beam hardening phenomenon, causing the first-order derivative of the projection data to show weak smoothness in a certain section, resulting in a jump in the projection data. After filtering, this weak smoothness will be further amplified, and eventually form a strip-shaped artifact of alternating light and dark in the reconstructed image. At the same time, due to the X-ray hardening problem, a nonlinear partial volume effect is generated, and the scattering phenomenon will be aggravated, all of which will cause distortion of the reconstructed image, especially forming a large amount of interference around the material.

[0083] There are many methods for removing artifacts, such as using an iterative reconstruction algorithm to remove metal artifacts, removing artifacts in the projection domain, and removing artifacts in the image domain. FIG4(B) illustrates an image after artifact removal and reconstruction. Compared with the uncorrected scan image shown in FIG4(A), the bright and dark bands caused by artifacts are removed.

[0084] Generally, the artifact removal function can be enabled only when deemed necessary by a physician, technician, or other personnel who views the scanned images of the diagnostic scan after visual inspection. In other words, the artifact removal function is enabled after an initial scanned image including a plurality of slice images is generated. Here, the initial scanned image is a set of slice images obtained by the diagnostic scan described above. However, conventional diagnostic scanned images only reconstruct the main area image within the scanning field of view of the CT device, and the image of the truncated area outside the scanning field of view of the CT device will not be reconstructed. When an object causing artifacts exists in the truncated area, it is difficult to start artifact removal reconstruction based on the main area image.

[0085] In view of this, the present disclosure provides a method for generating a CT image, which is capable of correctly enabling artifact removal reconstruction when an object causing artifacts exists within a truncation region. Figure 5 A flow chart illustrating an example process 500 for generating a CT image in accordance with the techniques of this disclosure is shown.

[0086] The process 500 begins at block 502. In block 502, projection measurement data of the subject 112 is acquired. The projection measurement data is from a diagnostic scan performed by the imaging system (CT device) 200. Specifically, the computing device 216 may 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 to perform a diagnostic scan on the subject 112 and acquire projection measurement data of an examination region of the subject 112.

[0087] In box 504, the initial scan image is reconstructed based on the projection measurement data obtained in box 502. As described above, when performing a diagnostic scan, the computing device 216 controls the x-ray radiation source 104 and the corresponding detector array 108 to move along a circle or arc around the subject 112, and at the same time controls the table 115 to move along the axial direction of the diagnostic scan through the table motor controller 226 to obtain projection measurement data of the examination area of ​​the subject 112. In the process of the subject 112 moving with the table 115, multiple sets of projection data can be acquired at certain time intervals, thereby reconstructing multiple slice images. Each slice image corresponds to a set of projection data, representing an image of a certain cross section along the axial direction in the examination area. Therefore, the reconstructed initial scan image includes multiple slice images.

[0088] In this embodiment, at least one of the reconstructed slice images includes a main area image within the field of view of the CT imaging system 100 and a truncated area image outside the scanning field of view of the CT device. The scanning field of view of the CT imaging system 100 is described below with reference to Figures 6(A) and 6(B). Figures 6(A) and 6(B) illustrate schematic diagrams of the scanning field of view of the CT imaging system 100. During the diagnostic scan, the x-ray radiation source 104 is controlled to move around the circumference or arc of the subject 112. The subject 112 lies on the workbench 115, so as to be located within the gantry aperture of the gantry 102. Figure 6(A) shows the situation where the x-ray radiation source 104 is at 0 degree and 90 degree positions in the circumferential direction, respectively. The x-ray radiation source 104 has a fixed (e.g., fan-shaped) radiation field, as shown by the x-ray beam 106 in the figure. Therefore, as the x-ray radiation source 104 moves circumferentially around the subject 112, the circular area formed by the intersection of the radiation fields at various positions is the scanning field of view of the CT imaging system 100, as shown by the dotted circle indicated by the arrow in the figure.

[0089] In the past, when reconstructing the projection measurement data of the diagnostic scan, only the main area image within the scanning field of view was reconstructed because the projection data of this part of the image is continuous. In other words, the x-ray radiation source 104 can generate projection measurement data within the scanning field of view at any angle relative to the subject 112. However, depending on factors such as the position and size of the subject 112, a part of the subject 112 may be in a truncated area outside the scanning field of view, as shown in part 112-1 in FIG6(A). The truncated area is defined by the radiation field of the x-ray radiation source 104, the scanning field of view, and the gantry aperture of the gantry 102.

[0090] The projection measurement data of the truncated area is discontinuous. For example, for part 112-1, when the x-ray radiation source 104 is located at the 0 degree position shown in FIG. 6(A), the complete projection measurement data cannot be obtained. When the x-ray radiation source 104 moves to the 90 degree position or the 300 degree position shown in FIG. 6(B), the projection measurement data of part 112-1 can be obtained. Therefore, although the projection measurement data of the diagnostic scan includes the projection measurement data of the main area image within the scanning field of view and the projection measurement data of the truncated area image outside the scanning field of view, in the past, only the projection measurement data of the main area image was reconstructed. The obtained initial scan image only includes the slice image corresponding to the main area image.

[0091] However, in this embodiment, when reconstructing the initial scan image, the projection measurement data of the truncated area outside the scanning field of view are simultaneously reconstructed to obtain a slice image containing both the main area image and the truncated area image.

[0092] Figure 7 The figure shows an example slice image in an initial scan image according to the technology of the present disclosure. Figure 7 In the example shown, circle A represents the scanning field of view. The image 301 within circle A is the main region (slice) image. In the truncated region outside the scanning field of view, a truncated region image 302 is also reconstructed. The truncated region image 302 can be reconstructed from the projection measurement data of the diagnostic scan.

[0093] The reconstruction of the truncated region image 302 can adopt any known or future developed algorithm, which is not limited herein. As an example, for example, the truncated projection data can be predicted by a mathematical model or a neural network, for example, the truncated portion can be predicted using a water model. Optionally, the projection measurement data can be preprocessed to reconstruct an initial image of the truncated portion. Then, based on the trained learning network, the initial image is calibrated to obtain a predicted image of the truncated portion. The preprocessing includes filling the truncated portion of the projection data. For example, the projection data information of the boundary of the untruncated portion can be filled into the truncated portion. Thus, the truncated region image 302 can be reconstructed based on the discontinuous partial data in the projection measurement data.

[0094] Back to Figure 5 In box 506, it is determined whether a specific type of substance exists in the multiple slice images reconstructed in box 504. As described above, the specific type of substance is a substance that causes image artifacts, such as metal. Since the initial scan image reconstructed by the present disclosure includes the main area image 301 within the scanning field of view and the truncated area image 302 outside the scanning field of view, in box 506, it is detected whether a specific type of substance exists in both the main area image 301 and the truncated area image 302.

[0095] There are many ways to detect this substance. For example, for a dense substance, it has a significant brightness compared to the surrounding voxels in the image. In this case, a simple threshold method can be used for detection. However, when the brightness difference between the substance and the surrounding voxels is small, such as when there are dense structures such as bones around metal, it is difficult to detect using the threshold method. In this case, deep learning can be used to improve the accuracy of detection. Figure 7 In the example, substance 303 may be detected.

[0096] In block 508 , it is determined whether substance 303 is detected in the truncated region image.

[0097] In response to determining in block 508 that a specific type of substance 303 exists in the truncated region image of the plurality of slice images reconstructed in block 504, an artifact removal reconstruction is performed on at least one slice image of the plurality of slice images in block 510. The artifact removal reconstruction is used to reduce or remove artifacts in the plurality of slice images caused by the substance 303.

[0098] If it is determined in box 508 that the specific type of material 303 does not exist in the truncated region image of the plurality of slice images reconstructed in box 504, the initial scan image reconstructed in box 504 is used as the final diagnostic scan image.

[0099] In this embodiment, when a specific type of substance 303 is detected in the truncated area of ​​the slice image, artifact removal reconstruction is automatically enabled. Doctors or technicians who view the slice image can directly obtain the scanned image after artifact removal and reconstruction, or both the scanned image after artifact removal and reconstruction and the initial scanned image. In addition, since the initial scanned image reconstructed by this embodiment includes both the main area image 301 within the scanning field of view and the truncated area image 302 outside the scanning field of view, when the substance 303 does not exist in the scanning field of view but is located in the truncated area, artifact removal reconstruction can be correctly enabled. In contrast, the previously reconstructed scanned image only includes the main area image 301. Therefore, when there is no substance 303 in the scanning field of view and there is substance 303 in the truncated area, artifact removal reconstruction will not be enabled. At this time, the substance 303 in the truncated area may still generate artifacts in the adjacent main area image 301. The use of the technology disclosed in the present invention can alleviate the situation where the main area image 301 is affected by the artifacts of the substance 303 in the truncated area. Figure 8 The figure shows a comparison of slice images before and after artifact removal and reconstruction according to the technology disclosed in the present invention, wherein the left side is a slice image of an initial scan image without artifact removal and reconstruction, and the right side is a corresponding slice image after artifact removal and reconstruction. It can be seen that the artifacts generated by the material 303 in the truncated area in the main area image 301 are faded.

[0100] Fig. 9 The figure shows a flow chart of an example process 900 for performing artifact removal reconstruction on a slice image according to the technology of the present disclosure. In box 902, the sub-region affected by the artifact in the slice image is determined. In particular, the inspection area and the truncation area are divided into multiple sub-regions. However, it is determined in which sub-regions of the inspection area and the truncation area the artifact appears. The location of the artifact and the extent of the artifact in the inspection area and the truncation area are determined, thereby defining the sub-region affected by the artifact. The determination of such artifacts can be carried out with the help of the characteristic characteristics of the determined image data and projection measurement data (such as attenuation or density values ​​in a specific area). In some embodiments, the sub-region affected by the artifact in which the artifact removal reconstruction will be performed subsequently can be defined based on the detected substance 303 and its location. This step can be performed, for example, according to the determined density (i.e., material density) at the corresponding position in the inspection area and the truncation area. Very dense areas indicate the presence of substance 303.

[0101] In some embodiments, the sub-region affected by the artifact may include the sub-region where the substance 303 is located and the sub-region near the substance 303. The sub-region near the substance 303 may be determined according to the desired artifact removal and reconstruction effect. For example, the sub-region near the substance 303 may be a sub-region adjacent to the sub-region where the substance 303 is located. In some embodiments, the sub-region near the substance 303 may be a sub-region within a certain range around the sub-region where the substance 303 is located.

[0102] In some embodiments, the sub-region near the substance 303 may be determined based on one or more of the following: the location of the substance 303, the type of the substance 303, the size of the substance 303, and the shape of the substance 303. This information may be obtained by detecting the initial scan image and the reconnaissance image described below.

[0103] In block 904, artifact removal is performed on the sub-region affected by the artifact to obtain an artifact-reduced sub-image. Only artifact-reduced sub-image data of the artifact-affected sub-region is generated. In case the artifact is a metal artifact, the artifact is corrected, for example, with the help of a so-called iMAR reconstruction method (iMAR-Iterative Metal Artifact Reduction). In general, artifact-reduced image reconstruction includes image reconstruction methods by which image artifacts can be reduced.

[0104] In box 906, at least a portion of at least one slice image is combined with the artifact-reduced sub-image to generate artifact-reduced image data of the initial scan image. The image data used for combination may be the following image data: in box 504 for generating the initial scan image, it has been reconstructed based on the acquired projection measurement data. The image used for combination with the artifact-reduced sub-image may be a sub-image of at least one artifact-free shadow area in the slice image. In some embodiments, the determination of the area or sub-area with artifacts is not performed after the reconstruction of the initial scan image, but is performed during the reconstruction of the initial scan image.

[0105] Fig.10 FIG. 1 is a flowchart of another example process 1000 for generating a CT image according to the technology of the present disclosure. In this embodiment, a reconnaissance scan is performed before a diagnostic scan, and a reconnaissance image obtained by the reconnaissance scan is used to detect a specific type of substance.

[0106] Specifically, in block 1002, at least one scout image of the object under examination (subject 112) is acquired at at least one flat scan angle. The "flat scan angle" here refers to the angle at which the x-ray radiation source 104 is viewed in the xy plane (reference Figure 1 ) relative to the subject 112, such as 0 degrees, 90 degrees, 300 degrees, etc. as shown in FIG. 6(A) and FIG. 6(B). As described above, the scout scan is a static scan performed by the x-ray radiation source 104 at a certain plain scan angle, and the obtained scout images are shown in, for example, FIG. 3(A) and FIG. 3(B). The radiation dose of the scout scan is relatively low, and it can be used to determine the inspection area targeted by the diagnostic scan.

[0107] In block 1004, an examination region of the subject 112 is determined based on the at least one scout image. In some embodiments, a three-dimensional boundary of the examination region may be determined based on two different unscanned (eg, orthogonal) angled scout images.

[0108] In box 1006, determine whether there is a substance 303 located in the inspection area or within a threshold range from the inspection area in at least one of the scout images. It should be noted here that the scout image is different from the reconstructed slice image. The scout image is an image obtained by plane scanning of the three-dimensional part of the subject 112, wherein the information of the three-dimensional voxels is superimposed on a plane image. The slice image is a tomographic scan of the three-dimensional part of the subject 112 along the axial direction, and each slice image contains information of a cross section of the three-dimensional part. Therefore, the scout image contains more overlapping voxel information than a single slice image. The substance 303 is more difficult to detect in the scout image than in the slice image. Therefore, in this embodiment, deep learning is used to detect the substance 303 from the scout image.

[0109] If the substance 303 is not detected in the reconnaissance image in block 1006, the reference Figure 5 The process 500 described, i.e., blocks 502, 504, 506, 508, and 510. In other words, a diagnostic scan is performed and the slice images obtained by the diagnostic scan are detected for the substance 303, especially the truncated area. This is because the scout image may not contain image information of the truncated area, depending on the flat scanning angle. Therefore, it is necessary to further detect the substance 303 on the slice image containing the truncated area image in block 506 to avoid the situation where the artifact removal reconstruction is not correctly enabled due to the appearance of the substance 303 in the truncated area.

[0110] If the presence of substance 303 in the scout image is detected in block 1006, it may be determined that artifact removal reconstruction will be performed on the slice image of the diagnostic scan. In this case, block 506 may be skipped and blocks 502, 504, and 510 may be performed. In some embodiments, the sub-region affected by the artifact in the slice image may be determined at the same time in block 504, as described in block 902. In some embodiments, block 506 may still be performed to determine whether other substances 303 exist in the truncated region. The position information of the other substances 303 detected in the truncated region may be used to improve the effect of artifact removal reconstruction.

[0111] Fig.11 FIG. 3 is a block diagram of an example image data reconstruction device 300 according to the technology of the present disclosure. The image data reconstruction device 300 can be used as Figure 2 216. Alternatively, the image data reconstruction device 300 may be a replacement for the image reconstructor 230. In some embodiments, the image data reconstruction device 300 may not be present in the imaging system 200, and instead the computing device 216 may perform one or more functions of the image data reconstruction device 300. In addition, the image data reconstruction device 300 may be located locally or remotely, and may be operably connected to the imaging system 200 using a wired or wireless network. In particular, an exemplary embodiment may use computing resources in a "cloud" network cluster for the image data reconstruction device 300.

[0112] The image data reconstruction device 300 has a data acquisition unit 301, which obtains data from the DAS 214 (refer to Figure 2 ) receives projection measurement data of the subject 112. The projection measurement data is forwarded to a reconstruction unit 302, which is configured to reconstruct a raw scan image based on the projection measurement data. The reconstructed raw scan image is then buffered in a buffer 304.

[0113] The image data reconstruction device 300 further includes a correction unit 303. The correction unit 303 includes a detection unit 3031 and an artifact removal reconstruction unit 3032. The detection unit 3031 detects the original scan image received from the reconstruction unit to determine whether a specific type of substance 303 exists in the plurality of slice images thereof. When the detection unit 3031 determines that the truncated region image in the slice image of the original scan image has substance 303, the artifact removal reconstruction unit 3032 performs artifact removal reconstruction on the slice image of the original scan image. To this end, the artifact removal reconstruction unit 3032 may be configured to perform Fig. 9 The process 900 shown. When combining at least a portion of at least one slice image with the artifact-reduced sub-image, at least a portion of the slice image to be combined with the artifact-reduced sub-image, such as a sub-image of an artifact-free shadow area, can be obtained from the cache 304. The generated (combined) artifact-reduced image data of the subject 112 is then output to the storage device 218 or the display 232 via the output interface 305.

[0114] In some embodiments, the data acquisition unit 301 may further execute block 1002 to acquire at least one scout image of the subject 112 at at least one flat scanning angle.

[0115] In some embodiments, the detection unit 301 may be further configured to determine whether there is a substance 303 in the at least one scout image that is located within the inspection region or within a threshold range from the inspection region. The artifact removal and reconstruction unit 3032 may be further configured to perform artifact removal and reconstruction on the at least one slice image when the detection unit 301 determines that there is a substance 303 in the at least one scout image that is located within the inspection region or within a threshold range from the inspection region.

[0116] The present disclosure also provides a computer tomography system, including a scanner unit, a control device, and a reference Fig.11 The image data reconstruction device 300 described herein. The scanner unit comprises a reference Figure 1 and Figure 2 The x-ray radiation source 104, the detector element 202 and the DAS 214 are described for collecting projection measurement data of the subject 112. The scanner unit is composed of a control device, such as reference Figure 2 The computing device 216 described above is controlled to acquire control signals so as to perform scanning according to a predetermined measurement protocol and acquire projection measurement data. The projection measurement data acquired by the scanner unit is further processed by the image data reconstruction device 300 to implement the processes described herein (processes 500, 900, 1000).

[0117] All or part of the implementation of the image data reconstruction device 300 can take the form of a computer program product that can be accessed from, for example, a computer (processor) usable or computer-readable medium. A computer-usable or computer-readable medium can be any device that can, for example, tangibly contain, store, transmit, or convey a program for use by any processor or in conjunction with any processor. The medium can be, for example, an electrical, magnetic, optical, electromagnetic, or semiconductor device. Other suitable media are also available. IV. Exemplary Computing Devices

[0118] Fig.12 FIG. 1 shows an example block diagram of a computing device 1200 according to the technology of the present disclosure. The computing device 1200 can be used as Figure 2 An example implementation of a computing device 216 is shown. The computing device 1200 includes: one or more processors 1220; a storage device 1210 for storing one or more programs, which, when executed by the one or more processors 1220, enable the one or more processors 1220 to implement the processes described in the present disclosure. The processor is, for example, a digital signal processor (DSP), a microcontroller, an application-specific integrated circuit (ASIC), or a microprocessor.

[0119] Fig.12 The computing device 1200 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0120] like Fig.12 As shown, computing device 1200 is in the form of a general computing device. Components of computing device 1200 may include, but are not limited to: one or more processors 1220, storage device 1210, and bus 1250 connecting different system components (including storage device 1210 and processor 1220).

[0121] Bus 1250 represents one or more of several types of bus structures, including a memory bus or memory controller, a foreign bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. For example, these architectures include but are not limited to Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus and Foreign Component Interconnect (PCI) bus.

[0122] The computing device 1200 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computing device 1200, including volatile and non-volatile media, removable and non-removable media.

[0123] Storage device 1210 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 1211 and / or cache memory 1212. Computing device 1200 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 1213 may be used to read and write non-removable, non-volatile magnetic media ( Fig.12 not shown, usually called a "hard drive"). Although Fig.12 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 the bus 1250 via one or more data medium interfaces. The storage device 1210 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 the various embodiments of the present invention.

[0124] A program / utility 1214 having a set (at least one) of program modules 1215 may be stored, for example, in the storage device 1210, such program modules 1215 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 may include an implementation of a network environment. The program modules 1215 generally perform the functions and / or methods of any embodiment described herein.

[0125] The computing device 1200 may also communicate with one or more external devices 1260 (e.g., keyboard, pointing device, display 1270, etc.), one or more devices that enable a user to interact with the computing device 1200, and / or any device that enables the computing device 1200 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 1230. Furthermore, the computing device 1200 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 1240. Fig.12 As shown, the network adapter 1240 communicates with other modules of the computing device 1200 via the bus 1250. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the computing device 1200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0126] The processor 1220 executes the programs stored in the storage device 1210 to perform various functional applications and data processing, such as implementing the process described in the present disclosure.

[0127] 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.

[0128] 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.

[0129] 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.

[0130] Instructions may also be further sent or received via a communication network using a transmission medium via a network interface device utilizing 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.).

[0131] 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 telephone network (e.g., a cellular network), a plain old telephone (POTS) network, and a wireless data network (e.g., a wireless network called 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.

[0132] 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.

[0133] So far, a method for generating a CT image and an image data reconstruction device according to the present invention are described, and a computer tomography system and a computer readable storage medium capable of implementing the method are also described.

[0134] According to the technology disclosed in the present invention, when reconstructing the projection measurement data of the diagnostic scan, the main area image within the scanning field of view of the CT device and the truncated area image outside the scanning field of view of the CT device are reconstructed at the same time, and the artifact removal reconstruction is enabled when the substance causing the artifact is detected in the truncated area image. Compared with the previous reconstruction of only the projection measurement data of the main area image, the influence of the artifact caused by the substance in the truncated area can be reduced or eliminated. When there is a substance causing the artifact in the truncated area, the artifact removal reconstruction can be correctly enabled.

[0135] 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 generating a CT image, comprising: Acquire projection measurement data of an object scanned by a CT device; Reconstructing an initial scan image based on the projection measurement data, wherein the initial scan image includes a plurality of slice images, at least one of the plurality of slice images includes a main region image within a scanning field of view of a CT device and a truncated region image outside a scanning field of view of the CT device; determining whether a specific type of material is present in the plurality of slice images; In response to determining that the substance exists in the truncated region image of the plurality of slice images, performing artifact removal reconstruction on at least one slice image of the plurality of slice images, the artifact removal reconstruction being used to remove artifacts in the plurality of slice images caused by the substance.

2. The method according to claim 1, characterized in that Performing the artifact removal reconstruction on at least one slice image among the plurality of slice images comprises: determining artifact-affected sub-regions in the slice image, wherein each of the artifact-affected sub-regions indicates the presence of at least one of the substances; performing the artifact removal on the sub-region affected by the artifact to obtain a sub-image with reduced artifacts; and At least a portion of the at least one slice image is combined with the artifact-reduced sub-image.

3. The method of claim 1, further comprising: Acquire at least one scout image of the inspection object at at least one flat scanning angle; as well as An examination region of the examination object is determined based on the at least one scout image.

4. The method according to claim 3, characterized in that The scout image is obtained by performing planar projection measurement on the object at one of the at least one flat scanning angles, and the projection measurement data is obtained by performing circumferential projection measurement on the inspection area of ​​the inspection object along the axial direction of the diagnostic scan.

5. The method of claim 3, further comprising: determining whether the substance is located within the inspection area or within a threshold range from the inspection area in the at least one scout image; as well as In response to determining that the substance exists in the at least one scout image within the examination region or within a threshold range from the examination region, the artifact removal reconstruction is performed on at least one slice image of the plurality of slice images.

6. The method according to claim 2, characterized in that Combining at least a portion of the at least one slice image with the artifact-reduced sub-image includes combining a sub-image of at least one artifact-free shadow region in the at least one slice image with the artifact-reduced sub-image.

7. The method according to claim 2, characterized in that The sub-region affected by the artifact includes the sub-region where the substance is located and the sub-region near the substance.

8. The method according to claim 7, characterized in that The substance includes a metallic substance.

9. The method according to claim 8, characterized in that The sub-region near the substance is also determined based on one or more of the following: the location of the substance; the type of substance in question; The size of the substance; and The shape of the substance.

10. The method according to claim 1, characterized in that It is determined whether the substance exists in each of the plurality of slice images by deep learning.

11. An image data reconstruction device, comprising: A data acquisition unit is configured to acquire projection measurement data of an object scanned by a CT device; a reconstruction unit configured to reconstruct an original scanned image based on the projection measurement data, wherein the original scanned image includes a plurality of slice images, at least one of the plurality of slice images includes a main region image within a scanning field of view of a CT device and a truncated region image outside a scanning field of view of the CT device; and A correction unit is configured to remove artifacts and reconstruct the original scanned image, and the correction unit comprises: a detection unit configured to determine whether a specific type of substance exists in the plurality of slice images; and An artifact removal and reconstruction unit is configured to perform artifact removal and reconstruction on at least one slice image among the multiple slice images in response to determining that the substance exists in the truncated area image among the multiple slice images, wherein the artifact removal and reconstruction is used to remove artifacts in the multiple slice images caused by the substance.

12. The image data reconstruction device according to claim 11, characterized in that: The artifact removal reconstruction unit is configured to: determining artifact-affected sub-regions in the slice image based at least on the locations of the substances, wherein each of the artifact-affected sub-regions indicates the presence of at least one of the substances; performing the artifact removal reconstruction on the sub-region affected by the artifact based at least on the position of the substance to obtain a sub-image with reduced artifacts; and At least a portion of the at least one slice image is combined with the artifact-reduced sub-image.

13. The image data reconstruction device according to claim 11, characterized in that: The data acquisition unit is further configured to acquire at least one scout image of the examination object at at least one flat scanning angle.

14. The image data reconstruction device according to claim 13, characterized in that: The scout image is obtained by performing planar projection measurement on the object at one of the at least one flat scanning angles, and the projection measurement data is obtained by performing circumferential projection measurement on the inspection area of ​​the inspection object along the axial direction of the diagnostic scan.

15. The image data reconstruction device according to claim 13, characterized in that: The detection unit is further configured to: determine whether the substance exists in the at least one reconnaissance image within the inspection area or within a threshold range from the inspection area, The artifact removal and reconstruction unit is further configured to: in response to determining that the substance exists in the at least one scout image within the examination region or within a threshold range from the examination region, perform the artifact removal and reconstruction on at least one slice image of the plurality of slice images.

16. The image data reconstruction device according to claim 12, characterized in that: The artifact removal reconstruction unit is further configured to combine at least one sub-image of an artifact-free shadow region in the at least one slice image with the artifact-reduced sub-image.

17. The image data reconstruction device according to claim 12, characterized in that: The sub-region affected by the artifact includes the sub-region where the substance is located and the sub-region near the substance.

18. The image data reconstruction device according to claim 17, characterized in that: The substance includes a metallic substance.

19. The image data reconstruction device according to claim 18, characterized in that: The sub-region near the substance is also determined based on one or more of the following: the location of the substance; the type of substance in question; The size of the substance; and The shape of the substance.

20. The image data reconstruction device according to claim 11, characterized in that: The detection unit is configured to determine whether the substance exists in each of the plurality of slice images through deep learning.

21. A computer tomography system comprising: A scanner unit configured to collect projection measurement data of the inspection object; a control device configured to control the scanner unit; as well as An image data reconstruction apparatus according to any one of claims 11 to 20.

22. A non-transitory machine-readable medium comprising a plurality of instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1-10.

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