Nuclear medicine diagnostic device and method, medical image processing device, and storage medium

Abstract

The nuclear medicine diagnostic apparatus of the embodiment includes a processing circuit. The processing circuit obtains simultaneous counting data including direct incident events to a gamma-ray detector and scattered events in an object; obtains the electron density function of the object and geometric information of the gamma-ray detector; infers a first probability value corresponding to the direct incident event of the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; reconstructs a PET image based on the first probability value, the second probability value and the simultaneous counting data. The processing circuit reconstructs the PET image based on a system matrix based on the first probability value and the second probability value.

Description

[0001] Reference to related applications

[0002] This application claims priority based on Japanese Patent Application No. 2021-058499 filed on March 30, 2021, the entire contents of which are cited herein. Technical Field

[0003] Embodiments of the present invention relate to a nuclear medicine diagnosis apparatus, a medical image processing apparatus, a nuclear medicine diagnosis method, and a non-transitory computer-readable storage medium. Background Art

[0004] Most current PET devices estimate the distribution of radiation in the subject and reconstruct images based on the direct incidence phenomenon, which is the detection phenomenon of gamma rays that enter the detector without being scattered in the subject. Usually, the algorithm for image reconstruction has a scattered ray correction function, but in many cases, the object of scattered ray correction is scattering up to the first scattering. However, when the object of scattered ray correction is scattering up to the first scattering, the image quality may be degraded.

[0005] On the other hand, in order to accurately perform scattered-ray correction for removing the detection phenomenon of multiply scattered low-energy gamma rays, a high-luminescence scintillator and a large number of light-receiving units corresponding to the high-luminescence scintillator are sometimes required.

[0006] In addition, for example, when high temporal resolution is desired in TOF (Time Of Flight)-PET, a scintillator that emits light for a short time is required, and a photodetector that requires each unit to respond quickly and recover in a short time is required. However, a scintillator that meets such conditions may become expensive. Summary of the invention

[0007] The technical problem to be solved by the present invention is to provide a nuclear medicine diagnosis device, a medical image processing device, a nuclear medicine diagnosis method and a non-temporary computer-readable storage medium capable of improving image quality.

[0008] Effects of the Invention

[0009] According to the nuclear medicine diagnostic device, medical image processing device, nuclear medicine diagnostic method and non-transitory computer-readable storage medium of the relevant technical solution, the image quality can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 It is a diagram showing an example of a nuclear medicine diagnostic apparatus according to an embodiment.

[0011] Figure 2 It is a diagram for explaining the background of the embodiment.

[0012] Figure 3 This is a diagram for explaining a processing circuit according to the first embodiment.

[0013] Figure 4 This is a flowchart illustrating the procedure of processing performed by the nuclear medicine diagnostic apparatus according to the first embodiment.

[0014] Figure 5 It is a diagram for explaining a processing circuit according to the second embodiment.

[0015] Figure 6 This is a flowchart illustrating the procedure of processing performed by the nuclear medicine diagnostic apparatus according to the second embodiment.

[0016] Figure 7 This is a diagram for explaining a processing circuit according to the third embodiment.

[0017] Figure 8 This is a flowchart illustrating the procedure of processing performed by the nuclear medicine diagnostic apparatus according to the third embodiment.

[0018] Fig. 9 This is a diagram for explaining a processing circuit according to the fourth embodiment.

[0019] Fig.10 This is a flowchart illustrating the procedure of processing performed by the nuclear medicine diagnostic apparatus according to the fourth embodiment. DETAILED DESCRIPTION

[0020] A nuclear medicine diagnostic device provided in one technical solution of the present invention is provided with a processing circuit. The processing circuit performs the following processing: obtaining simultaneous counting data, the simultaneous counting data including direct incident events to a gamma-ray detector and scattered events in an object; obtaining an electron density function of the object and geometric information of the gamma-ray detector; inferring a first probability value corresponding to the direct incident event of the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value and the simultaneous counting data. The processing circuit reconstructs the PET image according to a system matrix based on the first probability value and the second probability value.

[0021] Below, while referring to the attached Figure 1 Embodiments of a nuclear medicine diagnosis apparatus, a medical image processing apparatus, a nuclear medicine diagnosis method, and a program are described in detail.

[0022] (First embodiment)

[0023] Figure 1FIG. 2 is a diagram showing the structure of a PET device 100 as a nuclear medicine diagnostic device according to the embodiment. Figure 1 As shown, the PET apparatus 100 according to the embodiment includes a gantry apparatus 10 and a console apparatus 20 as a medical image processing apparatus. The gantry apparatus 10 includes a detector 1 , a timing information acquisition circuit 102 , a top board 103 , a bed 104 , and a bed driving unit 106 .

[0024] The detector 1 is a detector for detecting radiation by detecting scintillation light (fluorescence) which is light emitted when a substance in an excited state due to the interaction between annihilation gamma rays emitted from positrons in the subject P and a luminophore (scintillator) changes back to a ground state. The detector 1 detects energy information of radiation of annihilation gamma rays emitted from positrons in the subject P. The detector 1 is arranged in a plurality so as to surround the periphery of the subject P in a ring shape, and is composed of, for example, a plurality of detector blocks.

[0025] A specific example of the detector 1 is a photon counting type or Anger type detector, which includes a scintillator, a light detection element, and a light guide. That is, each pixel included in the detector 1 includes a scintillator and a light detection element for detecting generated scintillation light.

[0026] The scintillator converts the annihilation gamma rays emitted from the positrons in the subject P and incident thereon into scintillation light (scintillation photons, optical photons) and outputs the scintillator. The scintillator is formed of scintillator crystals suitable for TOF measurement and energy measurement, such as LaBr3 (Lanthanum Bromide), LYSO (Lutetium Yttrium Oxyorthosilicate), LSO (Lutetium Oxyorthosilicate), LGSO (Lutetium Gadolinium Oxyorthosilicate), or BGO, and is arranged in two dimensions, for example.

[0027] As the light detection element, for example, SiPM (Silicon photomultiplier) or photomultiplier tube is used. The photomultiplier tube has a photocathode that receives scintillation light and generates photoelectrons, a multistage dynode that provides an electric field to accelerate the generated photoelectrons, and an anode that serves as an outflow port for electrons, and multiplies the scintillation light output from the scintillator and converts it into an electrical signal.

[0028] Furthermore, the gantry device 10 generates count information based on the output signal of the detector 1 by the timing information acquisition circuit 102, and stores the generated count information in the storage unit 130 of the console device 20. The detector 1 is divided into a plurality of blocks and includes the timing information acquisition circuit 102.

[0029] The timing information acquisition circuit 102 converts the output signal of the detector 1 into digital data and generates counting information. The counting information includes the detection position, energy value and detection time of the annihilation gamma ray. For example, the timing information acquisition circuit 102 determines a plurality of light detection elements that convert scintillation light into electrical signals at the same timing. In addition, the timing information acquisition circuit 102 determines a scintillator number (P) representing the position of the scintillator into which the annihilation gamma ray is incident. The method for determining the position of the scintillator into which the annihilation gamma ray is incident can be determined by performing a centroid calculation based on the position of each light detection element and the intensity of the electrical signal. In addition, in the case where the element sizes of the scintillator and the light detection element correspond to each other, it is sufficient to determine the scintillator position into which the annihilation gamma ray is incident by the scintillator corresponding to the light detection element that obtains the output.

[0030] In addition, the timing information acquisition circuit 102 determines the energy value (E) of the annihilation gamma ray incident on the detector 1 by integrating the intensity of the electrical signal output from each light detection element. In addition, the timing information acquisition circuit 102 determines the detection time (T) when the detector 1 detects the scintillation light caused by the annihilation gamma ray. In addition, the detection time (T) can be either an absolute time or an elapsed time from the start time of imaging. In this way, the timing information acquisition circuit 102 generates counting information including the scintillator number (P), the energy value (E) and the detection time (T).

[0031] In addition, the timing information acquisition circuit 102 is implemented by circuits such as a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an application-specific integrated circuit (ASIC), a programmable logic device (such as a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). The timing information acquisition circuit 102 is an example of a timing information acquisition unit.

[0032] The top plate 103 is a bed on which the subject P is placed, and is arranged on the bed 104. The bed driving unit 106 moves the top plate 103 under the control of the bed control function 105k of the processing circuit 150. For example, the bed driving unit 106 moves the top plate 103 to move the subject P into the imaging port of the gantry device 10.

[0033] The console device 20 receives the operation of the PET device 100 by the operator, controls the imaging of PET images, and reconstructs the PET images using the counting information collected by the gantry device 10. Figure 1 As shown, the console device 20 includes a processing circuit 150, an input device 110, a display 120, and a storage unit 130. In addition, the various units included in the console device 20 are connected via a bus. The details of the processing circuit 150 will be described later.

[0034] The input device 110 is a mouse, keyboard, etc., which is used by the operator of the PET apparatus 100 to input various instructions and settings, and transfers the input various instructions and settings to the processing circuit 150. For example, the input device 110 is used to input an instruction to start imaging.

[0035] The display 120 is a monitor or the like that is referred to by the operator, and displays a respiratory waveform or a PET image of the subject under the control of the processing circuit 150 , or displays a GUI (Graphical User Interface) for accepting various instructions and settings from the operator.

[0036] The storage unit 130 stores various data used in the PET apparatus 100. The storage unit 130 is composed of a memory, for example, and is implemented by a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a hard disk, an optical disk, etc. The storage unit 130 stores counting information that is information corresponding to a scintillator number (P), an energy value (E), and a detection time (T), coincidence counting information that is information that is corresponding to a group of counting information and a sequence number of coincidence counting information, namely a coincidence number (coincidence NO.), and a reconstructed PET image, etc.

[0037] Next, the background of the embodiment will be described.

[0038] Most current PET devices estimate the distribution of radiation in the subject and reconstruct images based on the direct incidence phenomenon, which is the detection phenomenon of gamma rays that enter the detector without being scattered in the subject. Generally speaking, the algorithm for image reconstruction has a scattered ray correction function, but in many cases, the object of scattered ray correction is scattering up to the first scattering. However, when the object of scattered ray correction is scattering up to the first scattering, the image quality may be degraded.

[0039] For example, in Figure 2 In FIG. 1 , curve 30 is a graph showing the signal intensity of gamma rays incident on the detector as a function of energy. Region 32 is an energy region corresponding to direct incidence and single scattering. In contrast, region 31 is an energy region corresponding to multiple scattering. The energy region corresponding to multiple scattering, i.e., region 31, has a smaller signal intensity itself than the energy region corresponding to direct incidence and single scattering, i.e., region 32. In addition, since multiple phenomena are superimposed, the difficulty of scattering correction becomes higher.

[0040] As a method for performing scattered ray correction to remove the phenomenon of detecting low-energy gamma rays that have undergone multiple scattering with high accuracy, the following method can be considered: a scintillator with high light emission for accurately measuring incident energy and a large number of light receiving cells corresponding to the scintillator with high light emission are prepared. In this case, for example, when SiPM is used as a photodetector that converts scintillation photons into electrical signals, a large number of light receiving cells ranging from several thousand to tens of thousands are required to cope with high light emission scintillation.

[0041] In addition, when high temporal resolution is desired in TOF (Time Of Flight)-PET, for example, a scintillator is required to emit light for a short time, and a photodetector is required to have a quick response and a short recovery of each unit. In addition, an electronic circuit is required to calculate energy based on the signal in the subsequent stage of the photodetector, and in many cases, an ASIC suitable for the device needs to be developed.

[0042] Thus, in TOF-PET, when scattered light correction including multiple scattering is performed, the energy measurement system constituting one PET device 100 becomes complicated and becomes a system consisting of a large number of channels. In addition, since there are inherent deviations in the operation of each channel, in order to correct the deviations of these operations and obtain measurement accuracy, a complex sequence configuration must be implemented during operation. In addition, scintillators that simultaneously meet the conditions of high light emission and short light emission time required by TOF-PET become expensive.

[0043] Therefore, if the multi-scattering phenomenon can be effectively corrected without using a scintillator that satisfies the conditions of high light emission and short light emission time at the same time, the design constraints of the PET apparatus due to the energy measurement system can be greatly reduced.

[0044] The nuclear medicine diagnostic apparatus of the embodiment is a nuclear medicine diagnostic apparatus that corrects the multiple scattering phenomenon in the PET apparatus by a new method in view of this background. Specifically, the nuclear medicine diagnostic apparatus of the embodiment obtains the electron density function of the object and the geometric information of the gamma ray detector, and estimates the first probability value corresponding to the direct incident event and the second probability value corresponding to the scattering event including the multiple scattering event based on the acquired data, and reconstructs the PET image based on the estimated probability values ​​and the coincidence count data.

[0045] This can improve image quality or significantly reduce design constraints imposed by the energy measurement system of the PET device. For example, the PET device can be designed using a scintillator that is cheaper than the current situation, and the performance of the PET device can be improved.

[0046] Next, use Figure 3 and Figure 4 , the PET apparatus 100 according to the first embodiment will be described in detail. Figure 3 This is a diagram for explaining the configuration of the processing circuit 150 included in the PET apparatus 100 according to the first embodiment. Figure 4 This is a flowchart for explaining the processing performed by the PET apparatus 100 according to the embodiment.

[0047] like Figure 3 As shown, in the first embodiment, the processing circuit 150 has a detection data acquisition function 150a, a simultaneous counting information data generation function 150b, a geometric information acquisition function 150c, an electron density function acquisition function 150d, a direct incidence probability calculation function 150e, a scattered incidence probability calculation function 150f, a system matrix generation function 150g, an initial image generation function 150h, a reconstruction function 150i, a system control function 150j, and a bed control function 150k. In addition, for each function other than the system control function 150j and the bed control function 150k, the system control function 150j and the bed control function 150k are used. Figure 4 This will be described in detail later.

[0048] In the embodiment, each processing function performed by the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, the geometric information acquisition function 150c, the electron density function acquisition function 150d, the direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f, the system matrix generation function 150g, the initial image generation function 150h, the reconstruction function 150i, the system control function 150j, and the bed control function 150k is stored in the storage unit 130 in the form of a program executable by a computer. The processing circuit 150 is a processor that realizes the function corresponding to each program by reading the program from the storage unit 130 and executing it. In other words, the processing circuit 150 has a state in which each program is read out. Figure 3 The various functions represented within the processing circuit 150.

[0049] In addition, Figure 3 In the description, it is assumed that the processing functions of the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, the geometric information acquisition function 150c, the electron density function acquisition function 150d, the direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f, the system matrix generation function 150g, the initial image generation function 150h, the reconstruction function 150i, the system control function 150j, and the bed control function 150k are realized by a single processing circuit 150, but it is also possible to combine a plurality of independent processors to form the processing circuit 150, and realize the functions by executing programs by each processor. In other words, it is also possible that each of the above functions is constructed as a program, and one processing circuit 150 executes each program. As another example, it is also possible to install a specific function in a dedicated independent program execution circuit.

[0050] The term "processor" used in the above description refers to circuits such as a CPU (Central Processing Unit), a GPU (Graphical Processing Unit), an application-specific integrated circuit (ASIC), a programmable logic device (for example, a simple programmable logic device (SPLD), a complex programmable logic device (CPLD), and a field programmable gate array (FPGA)). The processor realizes its functions by reading and executing a program stored in the storage unit 130.

[0051] In addition, it is not limited to Figure 3 The processing circuit 150 described below Figure 5 , Figure 7 , Fig. 9 The processing circuit 150 can also be installed in the same way.

[0052] In addition, Figure 3 , the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, and the initial image generation function 150h are examples of the first acquisition unit. In addition, the geometric information acquisition function 150c and the electron density function acquisition function 150d are examples of the second acquisition unit. The direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f, and the system matrix generation function 150g are examples of the inference unit. The reconstruction function 150i is an example of the reconstruction unit. The system control function 150j and the bed control function 150k are examples of the control unit.

[0053] The processing circuit 150 controls the gantry device 10 and the console device 20 through the system control function 150j, thereby controlling the entire PET apparatus 100. For example, the processing circuit 150 controls imaging of the PET apparatus 100 through the system control unit 150j.

[0054] The processing circuit 150 controls the bed driving unit 106 through the bed control function 150 k.

[0055] Next, use Figure 4 , while explaining each function of the processing circuit 150, the flow of the processing performed by the PET device 100 related to the first embodiment is explained. In step S100, the processing circuit 150 obtains the electron density function of the object through the electron density function acquisition function 150d. As an example, the processing circuit 150 obtains a CT image of the object as the electron density function through the electron density function acquisition function 150d. As an example, the processing circuit 150 obtains a CT image of the object obtained as a result of imaging the object by a CT device (not shown) through the electron density function acquisition function 150d as the electron density function of the object. In addition, as another example, the nuclear medicine diagnostic device of the embodiment is a PET-CT device having a function as a CT device, and the processing circuit 150 may also obtain a CT image of the object obtained as a result of imaging the object by CT imaging of the PET-CT device through the electron density function acquisition function 150d.

[0056] In addition, the data representing the electron density function of the object is not limited to the data obtained by CT imaging. As an example, the data representing the electron density function of the object may also be a magnetic resonance image. For example, the processing circuit 150 uses the electron density function acquisition function 150d to image the object using an MRI device (not shown) and obtains, for example, a segmented magnetic resonance image as the electron density function of the object.

[0057] In this way, the PET apparatus 100 of the embodiment acquires the electron density function of the object separately from the data obtained by PET imaging in step S100 by the electron density function acquisition function 150d. Thus, the processing circuit 150 can acquire information that is the basis for estimating multiple scattering of gamma rays, and the accuracy of estimating multiple scattering in subsequent steps is improved compared with the conventional method.

[0058] Next, in step S110, the processing circuit 150 obtains geometric information of the detector 1 as a gamma ray detector by means of the geometric information acquisition function 150c. Here, the geometric information of the detector 1 refers to information on the relative positional relationship of each detector 1 and information on the positional relationship between the detector 1 and the subject P. As an example, the processing circuit 150 obtains information on the relative positional relationship of each detector 1 pre-stored in the storage unit 130 from the storage unit 130 by means of the geometric information acquisition function 150c, thereby obtaining information on the relative positional relationship of each detector 1. In addition, the processing circuit 150 obtains the position of the subject P via the bed driving unit 106 by means of the geometric information acquisition function 150c, thereby obtaining information on the positional relationship between the detector 1 and the subject P. In addition, for example, the order in which the processing of step S110 and the processing of step S100 are executed may be reversed. In addition, in the following description, Fig.10 Similarly, the processing of step S110 and the processing of step S100 may be performed in the opposite order.

[0059] Next, in step S120, the processing circuit 150 calculates a first probability value, which is a probability that the gamma ray directly enters the detector 1, through a direct incidence probability calculation function 150e, based on the electron density of the object acquired by the electron density function acquisition function 150d in step S100 and the geometric information of the detector 1 acquired by the geometric information acquisition function 150c in step S110. Here, the gamma ray directly enters the detector 1, which means that the number of scattering times of the generated gamma ray pair on the way to the detector 1 is 0.

[0060] In step S120, the processing circuit 150 performs calculations assuming that a unit radiation energy is radiated from each voxel set within the detector field of view. In step S150, the actual amount of radiation energy for each voxel is estimated.

[0061] The processing circuit 150 estimates a first probability value corresponding to a direct incidence event of the object when it is assumed that there is a unit radiation energy in a voxel within the field of view of the detector based on at least one of the electron density function of the object and the geometric information of the gamma-ray detector through the direct incidence probability calculation function 150e. As an example, the processing circuit 150 calculates the direct incidence probability to each detector 1, that is, the first probability value, when it is assumed that there is a unit radiation energy in a voxel within the field of view of the detector based on at least one of the electron density function of the object and the geometric information of the gamma-ray detector through, for example, a radiation transport equation, a Monte Carlo simulation, a neural network, etc.

[0062] Furthermore, the processing circuit 150 calculates the probability of the gamma ray entering the detector 1 through the scattered incident probability calculation function 150f based on the electron density of the object acquired by the electron density function acquisition function 150d in step S100 and the geometric information of the detector 1 acquired by the geometric information acquisition function 150c in step S110. Here, the so-called scattered includes both single scattering and multiple scattering.

[0063] In other words, the processing circuit 150 estimates the second probability value corresponding to the scattering event including the multiple scattering event in the object, assuming that there is a unit radiation energy in the voxel within the field of view of the detector, through the scattering incidence probability calculation function 150f, based on at least one of the electron density function of the object and the geometric information of the gamma-ray detector. Specifically, the processing circuit 150 calculates the scattering incidence probability of the detector 1, assuming that there is a unit radiation energy in the voxel within the field of view of the detector, through the scattering incidence probability calculation function 150f, for example, by using a radiation transport equation, a Monte Carlo simulation, a neural network, etc.

[0064] Next, the processing circuit 150 generates a system matrix H based on the direct incidence probability calculated by the direct incidence probability calculation function 150e and the scattered incidence probability calculated by the scattered incidence probability calculation function 150f through the system matrix generation function 150g. Here, the system matrix H is obtained by assuming that i is the response of the i-th LOR (Line Of Response) and j is the j-th voxel, and its elements are expressed as H ij Represents the matrix.

[0065] In addition, in the first and second embodiments, the scattering effect is expressed as a scattering matrix taken into the system matrix, but in the third embodiment, there is a difference that the scattering effect is expressed as a scattering term independent of the system matrix, for example, using a shifted Poisson model.

[0066] In step S130, the processing circuit 150 obtains count information from the timing information acquisition circuit 102. Specifically, the processing circuit 150 obtains the detection data of gamma rays from the timing information acquisition circuit 102 through the detection data acquisition function 150a. Here, the detection data of gamma rays obtained by the processing circuit 150 from the timing information acquisition circuit 102 through the detection data acquisition function 150a is, for example, count information including a scintillator number (P), an energy value (E), and a detection time (T). The count information includes both data due to direct incidence and data due to scattered incidence.

[0067] Next, the processing circuit 150 generates coincidence counting information data based on the counting information acquired by the detection data acquisition function 150a through the coincidence counting information data generation function 150b.

[0068] That is, in step S130 , the processing circuit 150 acquires coincidence count data including direct incident events on the gamma-ray detector 1 and scattered events in the subject P through the detection data acquisition function 150 a and the coincidence count information data generation function 150 b .

[0069] Next, in step S140, the processing circuit 150 sets the initial distribution of the radiation energy distribution of the object through the initial image generation function 150h. As an example, the processing circuit 150 performs an averaging operation on the PET images of multiple objects through the initial image generation function 150h to produce an average radiation energy distribution, and sets the average radiation energy distribution as the initial distribution. In addition, as another example, the processing circuit 150 sets the initial distribution in which a certain radiation energy is distributed in areas where the electron density is above a certain threshold value and no radiation energy is distributed in other areas in the CT image of the object obtained in step S100 through the initial image generation function 150h. In addition, as another example, the processing circuit 150 sets the electron density distribution calculated based on the CT image of the object obtained in step S100 as the initial distribution of the radiation energy distribution of the object through the initial image generation function 150h.

[0070] Next, in step S150, the processing circuit 150 estimates the radiation energy distribution of the object based on the initial distribution of the radiation energy of the object set in step S140, the system matrix generated in step S120, and the coincidence count data acquired in step S130, and reconstructs the PET image to generate a reconstructed image through the image reconstruction function 150i. In other words, the processing circuit 150 reconstructs the PET image based on the initial distribution of the radiation energy of the object set in step S140, the first probability value and the second probability value estimated in step S120, and the coincidence count data acquired in step S130 through the image reconstruction function 150i. As an example, the processing circuit 150 reconstructs the PET image based on the initial distribution of the radiation energy of the object set in step S140, the system matrix based on the first probability value and the second probability value estimated in step S120, and the coincidence count data acquired in step S130 through the image reconstruction function 150i. As an example, the processing circuit 150 uses the image reconstruction function 150i to infer the radiation energy distribution of the subject that will be reproduced by the simultaneous counting information obtained in step S130 based on the initial distribution of the radiation energy of the subject set in step S140 and the system matrix generated in step S120, and generates a reconstructed image.

[0071] Next, in step S160 , the processing circuit 150 causes the display 120 to display the reconstructed image generated in step S150 through the system control function 150 j .

[0072] As described above, in the first embodiment, the electron density function of the object and the geometric information of the gamma-ray detector are acquired, and based on the acquired data, the first probability value corresponding to the direct incident event and the second probability value corresponding to the scattered event including the multiple scattered event are estimated, and the PET image is reconstructed based on the estimated probability values ​​and the coincidence count data. According to the first embodiment, it is possible to configure a PET apparatus that performs imaging and reconstruction using the object information possessed by the scattered rays. In addition, by having the electron density function of the object and the geometric information of the gamma-ray detector, it is no longer necessary to install an expensive energy measurement circuit on the PET in order to measure the energy of the detected gamma rays, and the degree of freedom in design is improved.

[0073] As one example, a nuclear medicine diagnostic device that can obtain high-quality PET images using a scintillator that is cheaper than before can be manufactured. In addition, as another example, a scintillator having characteristics that are beneficial to the TOF function, such as a low light emission but a very rapid response to gamma ray incidence, can be used in the method of the embodiment, thereby widening the range of scintillators to be selected.

[0074] In addition, in the method related to the first embodiment, since the generated system matrix matches the scattering process and the attenuation process, there is no need to manually adjust the relative intensity between the scattering process and the attenuation process, as in the conventional method. In addition, in the method related to the first embodiment, since the image reconstruction is based on all phenomena including multiple scattering, an image with suppressed statistical noise can be obtained. In addition, in the method related to the first embodiment, low-radiation imaging due to low-dose quantification of radioactive drugs can be expected.

[0075] (Second embodiment)

[0076] Next, use Figure 5 and Figure 6 , the second embodiment is described. In the first embodiment, the case of obtaining the electron density function of the object and the geometric information of the gamma-ray detector, inferring the system matrix based on the obtained data, and reconstructing the PET image based on the inferred system matrix is ​​described. The second embodiment is also common in that the electron density function of the object and the geometric information of the gamma-ray detector are obtained, and the system matrix is ​​obtained based on the obtained data, but in detail, the system matrix is ​​obtained through steps different from those of the first embodiment. That is, the direct incident contribution in the system matrix is ​​a part that does not depend on the shape of the electron density function of the object, so the processing circuit separately pre-calculates the direct incident contribution in the system matrix, and then adds the scattered incident contribution to generate the system matrix. In this way, the calculation of the system matrix can be simplified.

[0077] exist Figure 5 The configuration of the processing circuit 150 according to the second embodiment is shown in FIG. Figure 5 In the embodiment, the functions other than the direct incidence probability calculation function 150e are the same as those in the first embodiment, so detailed description is omitted. Regarding the direct incidence probability calculation function 150e, in the first embodiment, the processing circuit 150 estimates the direct incidence probability using both the geometric information of the detector and the electron density function of the object, but in the second embodiment, the processing circuit 150 estimates the direct incidence probability using only the geometric information of the detector.

[0078] In addition, Figure 5 In, with Figure 3Similarly, the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, and the initial image generation function 150h are examples of the first acquisition unit. In addition, the geometric information acquisition function 150c and the electron density function acquisition function 150d are examples of the second acquisition unit. The direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f, and the system matrix generation function 150g are examples of the inference unit. The reconstruction function 150i is an example of the reconstruction unit. The system control function 150j and the bed control function 150k are examples of the control unit.

[0079] exist Figure 6 , a flow of processing executed by the PET apparatus 100 according to the second embodiment is shown. Here, the processing contents other than step S70, step S90, and step S120 are the same as those of the first embodiment, and therefore duplicate descriptions are omitted.

[0080] First, in step S70, the processing circuit 150 acquires the detector geometric information by the geometric information acquisition function 150c. The process of step S70 is the same as the process of step S110 in the first embodiment, but in the second embodiment, the process is performed at this timing.

[0081] Next, in step S90, the processing circuit 150 calculates the direct incidence probability as the first probability value based on the detector geometric information acquired by the geometric information acquisition function 150c in step S70 through the direct incidence probability calculation function 150e. At this time, the processing circuit 150 calculates the direct incidence probability as the first probability value without using the electron density function of the object through the direct incidence probability calculation function 150e. Next, in step S90, the processing circuit 150 calculates the contribution corresponding to the direct incidence probability as the first probability value in the system matrix based on the calculated first probability value through the system matrix generation function 150g. That is, the processing circuit 150 generates a system matrix of the direct incidence probability based on the detector geometric information through the system matrix generation function 150g.

[0082] Next, in step S100 and step S110 , the same processing as that in the first embodiment is performed, and the processing circuit 150 acquires the electron density function of the object through the electron density function acquisition function 150 d .

[0083] Next, in step S120, the processing circuit 150 performs the same processing as in the first embodiment by using the scattered incidence probability calculation function 150f to calculate the scattered incidence probability as the second probability value. Next, the processing circuit 150 generates a system matrix based on the direct incidence probability as the first probability value calculated in advance in step S90 and the scattered incidence probability as the second probability value calculated in step S120 as in the first embodiment by using the system matrix generation function 150g. Then, in steps S130 to S160, the same processing as in the first embodiment is performed.

[0084] Thus, in the second embodiment, the processing circuit 150 reconstructs the PET image by the reconstruction function 150i based on the system matrix based on the first probability value calculated in advance before obtaining the electron density function of the object. Thus, it is not necessary to calculate the direct incidence probability in the system matrix according to the object, and the calculation of the system matrix can be simplified. Thus, the calculation load in the reconstruction process can be reduced.

[0085] (Third embodiment)

[0086] In the first and second embodiments, the case where the scattering effect is expressed as a scattering matrix combined with the value of the system matrix is ​​described. However, the embodiment is not limited to this. In the third embodiment, for example, the case where the scattering effect is expressed as a correction term for the system matrix, that is, a scattering term, using a shifted Poission model or the like is described.

[0087] exist Figure 7 The configuration of the processing circuit 150 according to the third embodiment is shown in FIG. Figure 7 In the embodiment, functions other than the scatter term calculation function 1501 are the same as those of the second embodiment, and thus detailed descriptions thereof are omitted.

[0088] Here, j is used as a subscript to indicate the jth LOR, and the scatter term S calculated by the processing circuit 150 through the scatter term calculation function 1501 is j For example, it is given by the following formula (1).

[0089]

[0090] Here, i and m are the suffixes representing the i-th and m-th voxels, respectively, k is the suffix representing the k-th iteration in image reconstruction, and λ i k represents the estimated value of the radiant energy value of the i-th voxel in the k-th iteration, H ij represents the system matrix between the i-th voxel and the j-th LOR, g jis the number of events detected by the detector of the jth LOR. That is, the scatter term S calculated by the processing circuit 150 through the scatter term calculation function 1501 j It is a parameter regarding scattered rays, and is a correction term for the system matrix introduced for each LOR when reconstructing a PET image.

[0091] In addition, Figure 7 , the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, and the initial image generation function 150h are examples of the first acquisition unit. In addition, the geometric information acquisition function 150c and the electron density function acquisition function 150d are examples of the second acquisition unit. The direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f, and the system matrix generation function 150g are examples of the inference unit. The scattered term calculation function 150l is an example of the identification unit. The reconstruction function 150i is an example of the reconstruction unit. The system control function 150j and the bed control function 150k are examples of the control unit.

[0092] exist Figure 8 , a flow of processing executed by the PET apparatus 100 according to the third embodiment is shown. Here, the processing contents other than step S90, step S125, and step S150 are the same as those of the second embodiment, and therefore, duplicate descriptions are omitted.

[0093] Similar to the second embodiment, in step S90, the processing circuit 150 infers the direct incidence probability as the first probability value through the direct incidence probability calculation function 150e based on the detector geometric information obtained by the geometric information acquisition function 150c in step S70, and generates a system matrix based on the detector geometric information through the system matrix generation function 150g.

[0094] Here, in the third embodiment, unlike the second embodiment in which scattering is incorporated into the components of the system matrix, the effect of scattering is expressed as a correction term for the system matrix, i.e., a scattering term, and therefore does not become a component of the system matrix. Therefore, in step S90, the processing circuit 150 has already generated the system matrix by the system matrix generation function 150g.

[0095] In step S125, the processing circuit 150 calculates the probability that the gamma ray enters the detector after single scattering or multiple scattering, that is, the second probability, through the scattered incidence probability calculation function 150f based on the electron density of the subject obtained by the electron density function acquisition function 150d in step S100 and the geometric information of the detector 1 obtained by the geometric information acquisition function 150c in step S70.

[0096] In other words, the processing circuit 150 estimates the second probability value corresponding to the scattering event including the multiple scattering event in the object based on the electron density function of the object and the geometric information of the gamma-ray detector through the scattering incidence probability calculation function 150f. Specifically, the processing circuit 150 calculates the scattering incidence probability caused by the scattering event including the multiple scattering event through the scattering incidence probability calculation function 150f, for example, through the radiation transport equation, Monte Carlo simulation, neural network, etc. Next, the processing circuit 150 performs scattering calculation based on the detector geometric information obtained in step S70, the direct incidence probability as the first probability value estimated in step S90, the electron density function of the object obtained in step S100, and the initial estimated value of the radiation energy distribution of the object, and identifies the scattering term as a parameter about the scattered rays. Here, the scattering term as the parameter about the scattering term includes the multiple scattering term.

[0097] Furthermore, in step S150, the processing circuit 150 infers the value of the left side of equation (1) by evaluating the right side of equation (1) through the reconstruction function 150i, and infers the radiation energy distribution of the object based on the initial inferred value of the radiation energy distribution of the object set in step S140, the system matrix generated in step S90, and the scattering term as a parameter regarding the scattered rays generated in step S125, thereby reconstructing the PET image.

[0098] In addition, for example, the data acquired by the processing circuit 150 through the electron density acquisition function 150d in step S100 is not limited to the CT image, and may also be a magnetic resonance image. As an example, the processing circuit 150 performs segmentation processing on the magnetic resonance image through a segmentation function (not shown) to automatically extract / determine the part. Then, the processing circuit 150 converts the magnetic resonance signal value to the CT value for the magnetic resonance image according to the extracted / determined part, and generates a magnetic resonance image with a signal value similar to the CT image. The processing circuit 150 acquires the magnetic resonance image as an image representing the electron density of the object through the electron density acquisition function 150d.

[0099] Furthermore, the processing circuit 150 may perform, for example, semantic segmentation processing on the CT image of the subject acquired in step S100 by the system matrix generation function 150g to identify the scattering region and estimate the second probability value based on the identified scattering region. This can reduce the computational load associated with image reconstruction.

[0100] As described above, in the third embodiment, the processing circuit 150 calculates the scatter terms, which are parameters about scattered rays including multiple scattering, based on the detector geometry information and the electron density function by the scatter term calculation function 150i, and reconstructs the PET image using the separately calculated system matrix and scatter terms. In this way, by calculating and reconstructing the terms including multiple scattering as scatter terms independently from the system matrix, it is possible to accurately reconstruct the PET for data including scattering including multiple scattering.

[0101] (Fourth embodiment)

[0102] Next, the fourth embodiment is described. When generating simultaneous counting data, there is a case where a low-pass filter or a peak value (Japanese: wave height value) discriminator (discriminator) is used to remove noise from the output result from the gamma-ray detector to generate the simultaneous counting data. Here, for example, the value of the parameter used by the peak value discriminator for peak value cutoff may be different according to the detector. In the fourth embodiment, by performing image reconstruction according to the value of the parameter used for peak value cutoff in the detector, the image quality of the reconstructed PET image can be further improved.

[0103] exist Fig. 9 The configuration of the processing circuit 150 according to the fourth embodiment is shown in FIG. Fig. 9 In the embodiment, functions other than the cutoff processing function 150n and the cutoff parameter setting function 150m are the same as those of the first embodiment, and thus detailed descriptions thereof are omitted.

[0104] The cut-off processing function 150n is a function of performing noise reduction processing on the count data obtained by the detector data acquisition function 150a through a low-pass filter or a wave height discriminator (discriminator). As an example, the processing circuit 150 removes the count data less than the set peak value cut-off parameter from the count data obtained by the gamma ray detector data acquisition function 150a through the cut-off processing function 150n. For example, when the count data obtained by the detector data acquisition function 150a is less than the set peak value cut-off parameter, the output count data becomes 0.

[0105] Furthermore, the processing circuit 150 sets the value of the cutoff parameter through the cutoff parameter setting function 150m.

[0106] In addition, Fig. 9, the detection data acquisition function 150a, the simultaneous counting information data generation function 150b, the cutoff parameter setting function 150m, the cutoff processing function 150n and the initial image generation function 150h are examples of the first acquisition unit. In addition, the geometric information acquisition function 150c and the electron density function acquisition function 150d are examples of the second acquisition unit. The direct incidence probability calculation function 150e, the scattered incidence probability calculation function 150f and the system matrix generation function 150g are examples of the inference unit. The reconstruction function 150i is an example of the reconstruction unit. The system control function 150j and the bed control function 150k are examples of the control unit.

[0107] exist Fig.10 2 shows the flow of processing performed by the PET apparatus 100 according to the fourth embodiment. Here, the processing contents other than step S80, step S85, step S120, step S130, and step S150 are the same as those of the first embodiment, and thus repeated descriptions are omitted.

[0108] In step S80, the processing circuit 150 sets the peak value cutoff parameter through the cutoff parameter setting function 150m. In addition, in step S130, the processing circuit 150 obtains the detection data of gamma rays from the timing information acquisition circuit 102 as counting information through the detection data acquisition function 150a, as in the first embodiment. Next, the processing circuit 150 generates simultaneous counting information data based on the counting information obtained by the gamma ray detection data acquisition function 150a and the peak value parameter set in step S80 through the simultaneous counting information data generation function 150b. That is, the processing circuit 150 applies the peak value cutoff to the output result from the gamma ray detector through the simultaneous counting information data generation function 150b to generate simultaneous counting data.

[0109] On the other hand, in step S85 , the processing circuit 150 notifies the peak value cutoff parameter set in step S80 to the scattered incidence calculation units such as the direct incidence probability calculation function 150 e and the scattered incidence probability calculation function 150 f .

[0110] Furthermore, in step S120, the processing circuit 150 calculates the direct incidence probability through the direct incidence probability calculation function 150e and calculates the scattered incidence probability based on the scattered incidence probability calculation function 150f, but the processing circuit 150 estimates the direct incidence probability as the first probability value based on the value of the peak value parameter notified in step S85 through the direct incidence probability calculation function 150e. Furthermore, the processing circuit 150 estimates the scattered incidence probability as the second probability value based on the value of the peak value parameter notified in step S85 through the scattered incidence probability calculation function 150f.

[0111] Furthermore, the processing circuit 150 generates a system matrix based on the direct incidence probability calculated by the direct incidence probability calculation function 150e and the scattered incidence probability calculated by the scattered incidence probability calculation function 150f by the system matrix generation function 150g, but at this time, the system matrix is ​​generated based on the value of the peak value parameter notified in step S85. That is, the processing circuit 150 reflects the difference in the cutoff parameter of each detector in the system matrix generated in step S120.

[0112] In addition, in step S150, the processing circuit 150 uses the image reconstruction function 150i to infer the radiation energy distribution of the object, reconstruct the PET image, and generate a reconstructed image based on the initial distribution of the radiation energy of the object set in step S140, the system matrix generated in step S120, the simultaneous counting data obtained in step S130, and the peak value parameter set by the cutoff parameter setting function.

[0113] As described above, in the fourth embodiment, by performing scatter evaluation and image reconstruction using the value of the parameter for peak cutoff according to the detector, the image quality of the reconstructed PET image can be further improved.

[0114] According to at least one embodiment described above, image quality can be improved.

[0115] Regarding the above-mentioned embodiment, the following supplementary notes are disclosed as one aspect and optional features of the invention.

[0116] (Note 1)

[0117] The nuclear medicine diagnostic apparatus provided in one technical solution of the present invention comprises a first acquisition unit, a second acquisition unit, an inference unit and a reconstruction unit. The first acquisition unit acquires simultaneous counting data including direct incidence events to a gamma-ray detector and scattered events in a subject. The second acquisition unit acquires the electron density function of the subject and the geometric information of the gamma-ray detector. The inference unit infers a first probability value corresponding to the direct incidence event of the subject and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information. The reconstruction unit reconstructs a PET image based on the first probability value, the second probability value and the simultaneous counting data.

[0118] (Note 2)

[0119] The estimating unit may estimate the first probability value using a radiation transport equation, a Monte Carlo simulation, or a neural network.

[0120] (Note 3)

[0121] The estimating unit may estimate the second probability value using a radiation transport equation, a Monte Carlo simulation, or a neural network.

[0122] (Note 4)

[0123] The above scattering events may also include multiple scattering events.

[0124] The reconstruction unit may reconstruct the PET image based on a system matrix based on the first probability value.

[0125] (Note 5)

[0126] The reconstruction unit may reconstruct the PET image based on a system matrix based on the first probability value and the second probability value.

[0127] (Note 6)

[0128] The estimating unit may estimate the first probability value based on the geometric information, and estimate the second probability value based on the geometric information and the electron density function.

[0129] (Note 7)

[0130] The device may further include an identification unit that identifies parameters related to scattered rays based on the geometric information and the electron density function; and the reconstruction unit may reconstruct the PET image based on the parameters.

[0131] (Note 8)

[0132] The reconstruction unit may reconstruct the PET image using a shifted Poisson model.

[0133] (Note 9)

[0134] The first acquisition unit may generate the coincidence count data by applying a peak value cutoff to the output result from the gamma-ray detector;

[0135] The estimation unit estimates the first probability value and the second probability value based on the parameter for the peak value cutoff.

[0136] (Note 10)

[0137] The estimation unit may perform segmentation processing to identify the scattering region, and estimate the second probability value based on the identified scattering region. The segmentation processing may be semantic segmentation processing.

[0138] (Note 11)

[0139] The electron density function can also be a CT image.

[0140] (Note 12)

[0141] Electron density functions may also be generated based on magnetic resonance images.

[0142] (Note 13)

[0143] The medical image processing device provided in one technical solution of the present invention comprises a first acquisition unit, a second acquisition unit, an inference unit and a reconstruction unit. The first acquisition unit acquires simultaneous counting data including direct incident events to a gamma-ray detector and scattered events in a subject. The second acquisition unit acquires the electron density function of the subject and the geometric information of the gamma-ray detector. The inference unit infers a first probability value corresponding to the direct incident event of the subject and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information. The reconstruction unit reconstructs a PET image based on the first probability value, the second probability value and the simultaneous counting data. The reconstruction unit constructs the reconstructed PET image according to a system matrix based on the first probability value and the second probability value.

[0144] (Note 14)

[0145] The nuclear medicine diagnosis method provided in one technical solution of the present invention is a nuclear medicine diagnosis method performed by a nuclear medicine diagnosis device, comprising: obtaining simultaneous counting data including direct incident events to a gamma-ray detector and scattered events in a subject; obtaining the electron density function of the subject and the geometric information of the gamma-ray detector; inferring a first probability value corresponding to the direct incident event of the subject and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; reconstructing a PET image based on the first probability value, the second probability value and the simultaneous counting data. The method further comprises the following steps: constructing the reconstructed PET image based on a system matrix based on the first probability value and the second probability value.

[0146] (Note 15)

[0147] The program provided in one technical solution of the present invention enables a computer to perform the following processing: obtaining simultaneous counting data including direct incident events to a gamma-ray detector and scattered events in an object; obtaining the electron density function of the object and the geometric information of the gamma-ray detector; inferring a first probability value corresponding to the direct incident event of the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; reconstructing a PET image based on the first probability value, the second probability value and the simultaneous counting data. The above processing also includes the following processing: constructing the reconstructed PET image based on a system matrix based on the first probability value and the second probability value.

[0148] Several embodiments of the present invention have been described, but these embodiments are provided as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, changes, and combinations of the embodiments can be made without departing from the scope of the invention. These embodiments and their variations are included in the scope or spirit of the invention, and are included in the invention described in the claims and the scope of their equivalents.

Claims

1. A nuclear medicine diagnostic device, wherein: With processing circuit, The above processing circuit performs the following processing: Acquiring simultaneous counting data, the simultaneous counting data including direct incident events to the gamma-ray detector and scattering events including multiple scattering events in the object; Obtaining the electron density function of the above-mentioned object and the geometric information of the above-mentioned gamma-ray detector; inferring a first probability value corresponding to the direct incident event in the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value, and the coincidence count data, The processing circuit reconstructs the PET image based on a system matrix based on the first probability value and the second probability value.

2. The nuclear medicine diagnostic apparatus according to claim 1, wherein: The processing circuit estimates the first probability value based on the geometric information, and estimates the second probability value based on the geometric information and the electron density function.

3. The nuclear medicine diagnostic apparatus according to claim 1, wherein: The processing circuit generates the coincidence count data by applying a peak value cutoff to the output result from the gamma-ray detector, and estimates the first probability value and the second probability value based on a parameter for the peak value cutoff.

4. The nuclear medicine diagnostic apparatus according to claim 1, wherein: The processing circuit performs segmentation processing to identify a scattering region, and estimates the second probability value based on the identified scattering region.

5. A nuclear medicine diagnostic device, wherein: With processing circuit, The above processing circuit performs the following processing: Acquiring simultaneous counting data, the simultaneous counting data including direct incident events to the gamma ray detector and scattered events in the object; Obtaining the electron density function of the above-mentioned object and the geometric information of the above-mentioned gamma-ray detector; inferring a first probability value corresponding to the direct incident event in the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value, and the coincidence count data, The above scattering events include multiple scattering events, The processing circuit reconstructs the PET image according to a system matrix based on the first probability value. The processing circuit identifies parameters related to the scattered rays based on the geometric information and the electron density function, and reconstructs the PET image based on the parameters.

6. A medical image processing device, wherein: With processing circuit, The above processing circuit performs the following processing: Acquiring simultaneous counting data, the simultaneous counting data including direct incident events to the gamma-ray detector and scattering events including multiple scattering events in the object; Obtaining the electron density function of the above-mentioned object and the geometric information of the above-mentioned gamma-ray detector; inferring a first probability value corresponding to the direct incident event in the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value, and the coincidence count data, The processing circuit reconstructs the PET image based on a system matrix based on the first probability value and the second probability value.

7. A nuclear medicine diagnostic method, performed by a nuclear medicine diagnostic device, wherein: The steps include: Acquiring simultaneous counting data, the simultaneous counting data including direct incident events to the gamma-ray detector and scattering events including multiple scattering events in the object; Obtaining the electron density function of the above-mentioned object and the geometric information of the above-mentioned gamma-ray detector; inferring a first probability value corresponding to the direct incident event of the object and a second probability value corresponding to the scattering event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value, and the coincidence count data, The method further includes the following step: reconstructing the PET image according to a system matrix based on the first probability value and the second probability value.

8. A non-transitory computer-readable storage medium, wherein: Stores programs, The above program causes the computer to execute the following processing: Acquiring simultaneous counting data, the simultaneous counting data including direct incident events to the gamma-ray detector and scattering events including multiple scattering events in the object; Obtaining the electron density function of the above-mentioned object and the geometric information of the above-mentioned gamma-ray detector; inferring a first probability value corresponding to the direct incident event in the object and a second probability value corresponding to the scattered event based on at least one of the electron density function and the geometric information; and reconstructing a PET image based on the first probability value, the second probability value, and the coincidence count data, The program further causes the computer to execute a process of reconstructing the PET image based on a system matrix based on the first probability value and the second probability value.

Images