Spectrum image processing method, device and equipment and storage medium

Abstract

The application discloses a kind of spectral image processing method, device, equipment and storage medium. High temporal resolution image reconstruction method is used to the current first energy projection data is reconstructed to obtain at least two first energy images corresponding to different data acquisition time;Second energy projection data is reconstructed to obtain second target energy image, and the data acquisition time corresponding to the second energy projection data is taken as second target time;According to at least two first energy images corresponding to different data acquisition time and the data acquisition time corresponding to each first energy image, the first target energy image corresponding to the second target time is determined. The time mismatching problem existing in the spectral image of time-sharing acquisition is solved.

Description

Technical Field

[0001] This invention relates to the field of medical image processing technology, and in particular to an energy spectrum image processing method, apparatus, device, and storage medium. Background Technology

[0002] Currently, low- to mid-range energy-dispersive CT imaging systems can only achieve energy-dispersive imaging using slow tube voltage switching. However, energy-dispersive CT imaging systems that use slow tube voltage switching for energy-dispersive imaging cannot acquire spatially-temporally matched dual-spectral data. This makes it impossible to directly use the dual-spectral projection data acquired by the energy-dispersive CT system to determine the image of the target matrix material.

[0003] Existing technologies typically employ machine learning techniques to process the aforementioned dual-energy spectral data to determine high-energy and low-energy images with temporal correspondence. Then, based on the determined high-energy and low-energy images, image-domain material decomposition is performed to obtain the base material image.

[0004] Since the generalization ability of existing machine learning techniques is generally low, it is necessary to provide a technical solution with strong generalization ability to ensure the accuracy of determining high-energy images and low-energy images with time correspondence. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and storage medium for processing energy spectrum images to solve the time mismatch problem in time-division acquired energy spectrum images.

[0006] According to one aspect of the present invention, an energy spectrum image processing method is provided, comprising: A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. Image reconstruction is performed on the second energy projection data to obtain the second target energy image, and the data acquisition time corresponding to the second energy projection data is taken as the second target time. Based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each of the first energy images, the first target energy image corresponding to the second target time is determined.

[0007] According to another aspect of the present invention, an energy spectrum image processing apparatus is provided, comprising: The image reconstruction module uses a high temporal resolution image reconstruction method to reconstruct the current first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. The second image module is used to perform image reconstruction on the second energy projection data to obtain the second target energy image, and to take the data acquisition time corresponding to the second energy projection data as the second target time. The first image module is used to determine the first target energy image corresponding to the second target time based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image.

[0008] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the energy spectrum image processing method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the energy spectrum image processing method according to any embodiment of the present invention.

[0010] The technical solution of the energy spectrum image processing method provided in this embodiment of the invention determines at least two first energy images corresponding to the first energy projection data by using a high temporal resolution image reconstruction method, determines the second target energy image and the second target time corresponding to the second energy projection data, and determines the first target energy image corresponding to the second target time based on the at least two first energy images and the data acquisition time corresponding to each first energy image, thereby accurately and quickly determining the dual-energy spectrum image with time matching relationship.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of an energy spectrum image processing method provided according to an embodiment of the present invention; Figure 2A This is a schematic diagram of an energy spectrum image processing method provided according to an embodiment of the present invention; Figure 2B This is a schematic diagram of another energy spectrum image processing method provided according to an embodiment of the present invention; Figure 3A This is a schematic diagram of data usage in a high-resolution image reconstruction method provided according to an embodiment of the present invention; Figure 3B This is a schematic diagram of data usage in another high-resolution image reconstruction method provided according to an embodiment of the present invention; Figure 4 This is a flowchart of another energy spectrum image processing method provided according to an embodiment of the present invention; Figure 5 This is a flowchart of another energy spectrum image processing method provided according to an embodiment of the present invention; Figure 6A This is a schematic diagram of the energy spectrum image processing device provided in an embodiment of the present invention; Figure 6B This is a schematic diagram of the structure of another energy spectrum image processing device provided in an embodiment of the present invention; Figure 6C This is a schematic diagram of the structure of another energy spectrum image processing device provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of the C-arm CT imaging system implementing the embodiments of the present invention; Figure 8A This is a schematic diagram of the structure of another CT imaging system implementing an embodiment of the present invention; Figure 8B This is a schematic diagram of the structure of another CT imaging system implementing an embodiment of the present invention; Figure 9 This is a schematic diagram of the structure of an electronic device that implements an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] Figure 1 This is a flowchart of an energy spectrum image processing method provided in an embodiment of the present invention. This embodiment is applicable to the situation where a time-matched dual-energy spectrum image is determined based on dual-energy spectrum projection data that do not have a time-matching relationship. This method can be executed by an energy spectrum image processing device, which can be implemented in hardware and / or software, and can be configured in a processor. Figure 1 As shown, the method includes: S110. A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times.

[0017] When collecting energy spectrum data, low- to mid-range energy spectrum equipment typically collects projection data of one type of energy first, and then collects projection data of another type of energy at set idle intervals.

[0018] The high temporal resolution of high-temporal-resolution image reconstruction methods is relative to ordinary image reconstruction methods, such as FBP (filtered back projection). For any projection data, ordinary image reconstruction methods can produce one reconstructed image, while high-temporal-resolution image reconstruction methods can produce at least two reconstructed images, and the data acquisition times corresponding to these at least two reconstructed images are all distributed within the acquisition time range of the projection data.

[0019] The high temporal resolution image reconstruction method in this embodiment can be an iterative image reconstruction method based on finite angle reconstruction, such as total-variation, PICCS (Prior Image Constrained Compressed Sensing), spatial-temporal total-variation, SMART-RECON (Tomographic Image Reconstruction Based on Synchronous Removal of Multiple Artifacts), etc. It can also be an image domain deep learning method, a data consistency-constrained deep learning method, a data-image end-to-end deep learning method, or any one of weakly supervised, self-supervised, or unsupervised deep learning methods.

[0020] The first energy projection data can be either low-energy or high-energy. If the first energy projection data is low-energy, the second energy projection data is high-energy; conversely, if the first energy projection data is high-energy, the second energy projection data is low-energy. Users can choose the appropriate method based on their specific circumstances or image processing habits during energy spectrum image processing.

[0021] In one embodiment, in response to a first energy selection instruction, the corresponding low-energy projection data or high-energy projection data is used as the current first energy projection data. Specifically, the user selects low-energy projection data or high-energy projection data on the visual interactive interface through clicks or touches, and triggers a confirmation option. When the processor detects that the confirmation option has been triggered, it uses the selected low-energy projection data or high-energy projection data as the first energy projection data.

[0022] Optionally, in at least two first energy images, it is identified as i The first energy image corresponds to the group. i The projection data; wherein, the first energy projection data includes n Projected data for each group n The total number of first energy images is used as the data acquisition time corresponding to the projection data of each group, which is then taken as the first energy image corresponding to the first energy image. i Data collection time, i greater than or equal to 1 and less than or equal to 1 n integers, n It is an integer greater than or equal to 2.

[0023] In one embodiment, a high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain two first energy images, which correspond to the first data acquisition time and the second data acquisition time, respectively. For example... Figure 2AAs shown, the first energy projection data is low-energy projection data. After reconstructing the image using a high temporal resolution image reconstruction method, the corresponding first data acquisition time was obtained. The first energy image () ) and the corresponding second time acquisition time ( The first energy image () Or the first energy projection data is the high-energy projection data (). The image was reconstructed using a high temporal resolution image reconstruction method to obtain the corresponding first data acquisition time. The first energy image of ) ) and the corresponding second time acquisition time ( The second energy image () ).

[0024] Wherein, corresponding to the first data acquisition time ( Figure 2B T in L1 or T H1 The first energy image is composed of the first half of the first energy projection data (projection data). Figure 3A The left arc or Figure 3B The left arc was reconstructed, corresponding to the second data acquisition time ( Figure 2B T in L2 or T H2 The first energy image is composed of the latter half of the first energy projection data (projection data). Figure 3A The right arc or Figure 3B The data was reconstructed from the right-hand arc. The data acquisition time corresponding to the first half of the projection data is earlier than the data acquisition time corresponding to the second half of the projection data, that is, the first data acquisition time is earlier than the second data acquisition time.

[0025] In this embodiment, the midpoint of the data acquisition time corresponding to the projected data is taken as the data acquisition time corresponding to the projected data. For example, if the projected data M is acquired within the data acquisition time [time A, time B], then the midpoint between time A and time B is taken as the data acquisition time corresponding to the projected data.

[0026] In one embodiment, a high temporal resolution image reconstruction method is used to reconstruct the current first energy projection data to obtain at least three first energy images corresponding to different data acquisition times.

[0027] S120. Perform image reconstruction on the second energy projection data to obtain the second target energy image, and take the data acquisition time corresponding to the second energy projection data as the second target time.

[0028] The second energy projection data is reconstructed using existing image reconstruction methods to obtain the second target energy image. The data acquisition time corresponding to the second energy projection data is taken as the second target time corresponding to the second target energy image.

[0029] Since the second target energy image is reconstructed based on the second energy projection data, and the second target time is the data acquisition time corresponding to the second energy projection data, the second target time is also the data acquisition time corresponding to the second target energy image.

[0030] Since the first energy projection data and the second energy projection data were not collected simultaneously, the time of the second target is different from the data acquisition time corresponding to the above-mentioned at least two first energy images.

[0031] S130. Based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image, determine the first target energy image corresponding to the second target time.

[0032] In one embodiment, the number of the at least two first energy images is 2. Based on the two first energy images and the data acquisition time corresponding to the two first energy images respectively, the first energy image corresponding to the second target time is determined by time domain interpolation method, and the first energy image is used as the first target energy image.

[0033] In one embodiment, the number of at least two first energy images is greater than or equal to three. At least two image combinations from the at least three first energy images are determined, each image combination including two first energy images. Based on the two first energy images in each image combination and the data acquisition time corresponding to each of the two first energy images, a first reference target energy image corresponding to the current second target time is determined using a time-domain interpolation method. The first target energy image corresponding to the second target time is determined based on all the first reference target energy images; for example, a weighted sum of all the first reference target energy images is used to obtain the first target energy image. This embodiment improves the accuracy of determining the first target energy image by using multiple image combinations.

[0034] Since the data acquisition time corresponding to the first target energy image and the second target energy image is the same as the second target time, the two have a good time matching relationship.

[0035] The technical solution of the energy spectrum image processing method provided in this embodiment of the invention determines at least two first energy images corresponding to the first energy projection data by using a high temporal resolution image reconstruction method, determines the second target energy image and the second target time corresponding to the second energy projection data, and determines the first target energy image corresponding to the second target time based on the at least two first energy images and the data acquisition time corresponding to each first energy image, thereby accurately and quickly determining the dual-energy spectrum image with time matching relationship.

[0036] Figure 4 This is a flowchart of another energy spectrum image processing method provided in an embodiment of the present invention, including: S210. A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times.

[0037] S220. Perform image reconstruction on the second energy projection data to obtain the second target energy image, and take the data acquisition time corresponding to the second energy projection data as the second target time.

[0038] S230. Based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image, determine the first target energy image corresponding to the second target time.

[0039] S240. Determine a set of target base material images corresponding to the second target time based on the first target energy image and the second target energy image.

[0040] Since both the first target energy image and the second target energy image correspond to the second target time, the target base material image corresponding to the second target time, such as the water-iodine image, can be accurately determined based on the first target energy image and the second target energy image.

[0041] like Figure 2A and Figure 2B As shown, it can be based on the first target energy image ( ,by Figure 2B Hollow circle representation within high-energy regions and energy image of the second target ( ,by Figure 2B The solid circle representation within the high-energy region determines the time corresponding to the second target (T). H The target base material image, the base material combination including the first base material image ( ) and the image of the second basic substance ( It can also be based on the energy image of the first target (). ,by Figure 2B (represented by solid circles in the low-energy region) and the energy image of the second target ( ,by Figure 2B The hollow circle representation in the low-energy region determines the time corresponding to the second target moment (T). L The target base material image, the base material combination including the first base material image ( Images of the second basic material ( ).

[0042] The technical solution provided by the embodiments of the present invention has high accuracy because both the first target energy image and the second target energy image correspond to the second target time. Therefore, a set of target base material images determined based on the two images has high accuracy, thus achieving the technical effect of improving the accuracy of target base material image determination.

[0043] Figure 5 This is a flowchart of another energy spectrum image processing method provided in an embodiment of the present invention, including: S310. A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times.

[0044] S320. Perform image reconstruction on the second energy projection data to obtain the second target energy image, and take the data acquisition time corresponding to the second energy projection data as the second target time.

[0045] S330. Based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each of the first energy images, determine the first target energy image corresponding to the second target time.

[0046] S340. In response to the energy switching command, switch the projection data corresponding to the first energy projection data and the second energy projection data respectively, and return to the step of performing image reconstruction on the first energy projection data using a high temporal resolution image reconstruction method until a set of target base material images corresponding to the new second target time is obtained.

[0047] The energy switching command can be used to switch the roles of high-energy projection data and low-energy projection data in the target substrate image determination process. For example, when the first energy projection data is low-energy projection data, the second energy projection data is high-energy projection data; in response to the energy switching command, the first energy projection data becomes high-energy projection data, and the second energy projection data becomes low-energy projection data.

[0048] In one embodiment, the energy switching command can be manually triggered by the user; alternatively, it can be automatically generated upon detecting the generation of an image of the target substrate. This embodiment addresses user operational needs in different scenarios through two triggering methods.

[0049] After the energy switch, according to the above steps, the first target energy image and the second target energy image corresponding to the data acquisition time (new second target time) corresponding to the second energy projection data are determined, and a set of target base material images are determined based on the first target energy image and the second target energy image.

[0050] S350. Determine the dynamic change results of the target substance concentration distribution based on the two sets of target base substance images and the second target time corresponding to the two sets of target base substance images respectively.

[0051] Since the data acquisition times corresponding to the first energy projection data and the second energy projection data are different, the second target time corresponding to the second energy projection data is different from the second target time corresponding to the first energy projection data. Therefore, the dynamic change results of the target substance concentration distribution can be determined based on the two sets of target base material images and the second target time corresponding to each pair of target base material images.

[0052] In this embodiment of the invention, users can switch the roles of high-energy projection data and low-energy projection data in the target base material image determination process through energy switching commands, thereby determining a new set of target base material images. Based on the two sets of target base material images determined before and after energy switching, as well as the second target time corresponding to each pair of target base material images, the dynamic change results of the target material concentration distribution are determined. The operation is simple and fast.

[0053] Figure 6A This is a schematic diagram of the energy spectrum image processing device provided in an embodiment of the present invention. Figure 6A As shown, the device includes: The image reconstruction module 610 uses a high temporal resolution image reconstruction method to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. The second image module 620 is used to perform image reconstruction on the second energy projection data to obtain the second target energy image, and to take the data acquisition time corresponding to the second energy projection data as the second target time. The first image module 630 is used to determine the first target energy image corresponding to the second target time based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image.

[0054] In one embodiment, such as Figure 6B As shown, the device also includes: The base material image module 640 is used to determine a set of target base material images corresponding to the second target time based on the first target energy image and the second target energy image.

[0055] In one embodiment, it is identified as i The first energy image corresponds to the group as follows: i Projection data; The first energy projection data includes n The projection data for each group n The total number of the first energy images is used as the data acquisition time corresponding to the projection data of each group, and the data acquisition time corresponding to the first energy image is taken as the data acquisition time of the corresponding first energy image. i greater than or equal to 1 and less than or equal to 1 n integers, n It is an integer greater than or equal to 2.

[0056] In one embodiment, the first image module is specifically used for: Based on the time-domain interpolation method, the first target energy image corresponding to the second target time is determined according to at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image.

[0057] In one embodiment, the device further includes: The energy selection module is used to respond to the first energy selection command by using the corresponding low-energy projection data or high-energy projection data as the first energy projection data and the projection data of another energy as the second energy projection data.

[0058] In one embodiment, as shown in FIG6C, the device further includes an energy switching module 650 and a dynamic result module 660; The energy switching module 650 is used for: In response to the energy switching command, the projection data corresponding to the first energy projection data and the second energy projection data are switched respectively, and the step of reconstructing the image of the first energy projection data using the high temporal resolution image reconstruction method is returned until a set of target base material images corresponding to the second target time is obtained. The Dynamic Results Module 660 is used for: The dynamic changes in the concentration distribution of the target substance are determined based on two sets of target substance images and the second target time corresponding to each of the two sets of target substance images.

[0059] The technical solution of the energy spectrum image processing device provided in this embodiment of the invention determines at least two first energy images corresponding to the first energy projection data by using a high temporal resolution image reconstruction method, determines the second target energy image and the second target time corresponding to the second energy projection data, and determines the first target energy image corresponding to the second target time based on the at least two first energy images and the data acquisition time corresponding to each first energy image, thereby accurately and quickly determining the dual-energy spectrum image with time matching relationship.

[0060] The energy spectrum image processing apparatus provided in the embodiments of the present invention can execute the energy spectrum image processing method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0061] Figure 7 This is a schematic diagram of the C-arm CT imaging system provided in an embodiment of the present invention. The system includes a gantry 1211, a detector 1212, a bed 1214, an X-ray tube 1215, a C-arm drive shaft 1216, a rotating shaft 1217, and a base 1219. The X-ray tube 1215 and the detector 1212 are mounted at both ends of the C-gantry 1211, with their center connection line perpendicular to its rotation axis 1218. The C-gantry 1211 rotates around the rotation axis 1218, thereby capturing image data of the patient 1213 on the bed 1213 at different projection angles. The X-ray tube 1215's current, voltage, and exposure time are controlled by an X-ray generator 123. The projection data acquired by the detector 1212 is transmitted to a computer via a communication system 126. The gantry 1211 is connected to the C-arm drive shaft 1216, whose power is provided by the rotating shaft 1217. The base 1219 bears the weight. The C-arm control unit 121 controls the rotational speed, angle, and position of the gantry 1211. The spindle control unit 122 connects to the base 1219 and provides power to the entire C-arm system. The X-ray generator 123 controls the current, voltage, and exposure time of the X-ray tube 1215. For example, by controlling the voltage of the X-ray tube 1215, it controls the output of X-rays of a first energy. After the first energy projection data corresponding to the first energy X-ray is acquired, after a set idle time interval, it controls the output of X-rays of a second energy by controlling the voltage of the X-ray tube 1215 until the second energy projection data corresponding to the second energy X-ray is acquired. The data acquisition system 124 coordinates the gantry 1211, detector 1212, and X-ray tube 1215, and collects the acquired data. The bed board control system 125 controls the position and movement speed of the bed board 1214 to achieve different scanning tracks for the patient 1213. The communication system 126 connects the C-arm control unit 121, the spindle control unit 122, the X-ray generator 123, the data acquisition system 124, and the bed control system 125, and transmits the acquired projection data to the memory of the computer device 2.

[0062] Figure 8A and Figure 8BA schematic diagram of another CT imaging system is shown. This CT imaging system is a diagnostic spectral CT device. Compared to a C-arm CT, its gantry 1211 is ring-shaped. The detector 1212 and X-ray tube 1215 are both mounted on the gantry and are relatively distributed. The bed plate 1214 moves in and out of the gantry aperture under the control of the bed plate control system 125. The gantry drives the detector 1212 and X-ray tube 1215 to move around the bed plate 1214. The X-ray generator 123 controls the current, voltage, and exposure time of the X-ray tube 1215. For example, by controlling the voltage of the X-ray tube 1215, it controls the output of X-rays of a first energy. After the first energy projection data corresponding to the first energy X-ray is acquired, after a set idle time interval, the voltage of the X-ray tube 1215 is controlled to control the output of X-rays of a second energy until the second energy projection data corresponding to the second energy X-ray is acquired.

[0063] Figure 9 This is a schematic diagram of the structure of a computer device provided in another embodiment of the present invention, as shown below. Figure 9 As shown, the computer device 2 includes a processor 201, a memory 202, an input device 203, and an output device 204; the number of processors 201 in the device can be one or more. Figure 9 Taking a processor 201 as an example; the processor 201, memory 202, input device 203, and output device 204 in the device can be connected via a bus or other means. Figure 9 Taking the example of a connection between China and Israel via a bus.

[0064] The memory 202, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the energy spectrum image processing method in this embodiment of the invention (e.g., image reconstruction module 61, second image module 62, and first image module 63). The processor 201 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 202, thereby implementing the aforementioned energy spectrum image processing method.

[0065] The memory 202 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, the memory 202 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 202 may further include memory remotely located relative to the processor 201, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0066] Input device 203 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. This input device can be configured in an operator workstation, through which the operator controls the operation of the CT imaging system.

[0067] The output device 204 may include a display device such as a display screen, for example, the display screen of an operation workstation.

[0068] Another embodiment of the present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform an energy spectrum image processing method, the method comprising: A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. Image reconstruction is performed on the second energy projection data to obtain the second target energy image, and the data acquisition time corresponding to the second energy projection data is taken as the second target time. Based on the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each of the first energy images, the first target energy image corresponding to the second target time is determined.

[0069] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0070] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for processing energy spectrum images, characterized in that, include: A high temporal resolution image reconstruction method is used to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. Image reconstruction is performed on the second energy projection data to obtain the second target energy image, and the data acquisition time corresponding to the second target energy image is taken as the second target time. Based on the time-domain interpolation method, the first target energy image corresponding to the second target time is determined according to the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image.

2. The method according to claim 1, characterized in that, Also includes: Based on the first target energy image and the second target energy image, a set of target base material images corresponding to the second target time are determined.

3. The method according to claim 1, characterized in that, Identified as i The first energy image corresponds to the group as follows: i Projection data; The first energy projection data includes n The projection data for each group n The total number of the first energy images is used as the data acquisition time corresponding to the projection data of each group, and the data acquisition time corresponding to the first energy image is taken as the data acquisition time of the corresponding first energy image. i greater than or equal to 1 and less than or equal to 1 n integers, n It is an integer greater than or equal to 2.

4. The method according to claim 1 or 2, characterized in that, Before performing image reconstruction on the first energy projection data using the high temporal resolution image reconstruction method, the method further includes: In response to the first energy selection command, the corresponding low-energy projection data or high-energy projection data is used as the first energy projection data, and the projection data of another energy is used as the second energy projection data.

5. The method according to claim 2, characterized in that, After the target base material image is determined, the following steps are also included: In response to the energy switching command, the projection data corresponding to the first energy projection data and the second energy projection data are switched respectively, and the step of reconstructing the image of the first energy projection data using the high temporal resolution image reconstruction method is returned until a set of target base material images corresponding to the new second target time is obtained. The dynamic changes in the concentration distribution of the target substance are determined based on two sets of target substance images and the second target time corresponding to each of the two sets of target substance images.

6. An energy spectrum image processing device, characterized in that, include: The image reconstruction module uses a high temporal resolution image reconstruction method to reconstruct the first energy projection data to obtain at least two first energy images corresponding to different data acquisition times. The second image module is used to perform image reconstruction on the second energy projection data to obtain the second target energy image, and to take the data acquisition time corresponding to the second target energy image as the second target time. The first image module is used to determine the first target energy image corresponding to the second target time based on the time domain interpolation method, according to the at least two first energy images corresponding to different data acquisition times and the data acquisition time corresponding to each first energy image.

7. The apparatus according to claim 6, characterized in that, Also includes: The base material image module is used to determine the target base material image corresponding to the second target time based on the first target energy image and the second target energy image.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the energy spectrum image processing method according to any one of claims 1-5.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the energy spectrum image processing method according to any one of claims 1-5.

Images