CN114140546A

CN114140546A - Image reconstruction method, image reconstruction device, storage medium, image generation method and imaging system

Info

Publication number: CN114140546A
Application number: CN202111426454.1A
Authority: CN
Inventors: 李鑫宇; 李昂; 母登云; 黄晶
Original assignee: Raysolution Digital Medical Imaging Co ltd; Huazhong University of Science and Technology
Current assignee: Raysolution Digital Medical Imaging Co ltd; Huazhong University of Science and Technology
Priority date: 2021-11-27
Filing date: 2021-11-27
Publication date: 2022-03-04
Also published as: WO2023092534A1

Abstract

The invention relates to an image reconstruction method, an image reconstruction device, a storage medium, a generation method and an imaging system. The method comprises the following steps; acquiring scanning data of an imaging target; judging whether DOI information exists in the scanning data, and if so, applying the DOI information to image reconstruction; and if the DOI information does not exist, reconstructing the image by using the system response matrix. By utilizing DOI information, image reconstruction algorithm support facing different demand scenes is constructed, so that reconstructed images meeting different demands are obtained, and the problem of retraction during image reconstruction is solved.

Description

Image reconstruction method, image reconstruction device, storage medium, image generation method and imaging system

Technical Field

The present invention relates to the field of image reconstruction, and in particular, to an image reconstruction method, an image reconstruction device, a storage medium, a generation method, and an imaging system.

Background

In a high-energy photon detection system, such as a pet (positron emission tomography) system, due to the influence of Depth of Interaction (DOI), a reconstructed image may be shifted toward the center of a Field of View (FOV) due to the following reasons: the positron and the negative electron emitted by the source are annihilated to produce a pair of oppositely directed, equal-energy gamma photons, which are then incident on a detector comprising a crystal array. Because each gamma photon has a different probability of causing physical effects such as photoelectric effect, compton scattering, etc. from the crystal, and the resulting energy loss is different, the photons may be deposited at different depths in the crystal. Because of the compact arrangement and small size of the crystals in the detector, the phenomenon of transmission between crystals is likely to occur, i.e. gamma photons penetrate the crystal that was initially driven into and are eventually deposited in the surrounding crystals. As shown in fig. 1, a gamma photon should be deposited in crystal 1, but the physical effect occurring in crystal 1 does not fully dissipate its energy, so it passes out of crystal 1 and eventually deposits at position a in crystal 2.

Two gamma photons are considered to be generated by the annihilation of the same positron when they are within a certain range of time (time window) and within a certain range of energy (energy window). Since the detector only records the final deposition position of the gamma photon, the Line of the centers of the surfaces of the crystals, where two gamma photons are currently deposited, connected with a 'B' is taken as a Response Line (LOR), that is, the position where the positron annihilation occurs is regarded as a certain position on the LOR. However, in practice, the positron is annihilated on the line AB, and if uncorrected, it is biased to cause a parallax effect.

The present application aims to establish a method for systematically solving parallax effect and an implementation system.

Disclosure of Invention

In order to solve the above problems, a first object of the present invention is to provide an image reconstruction method, including the steps of: acquiring scanning data of an imaging target; judging whether DOI information exists in the scanning data; wherein the DOI information is used to locate the deposition location of the photons in the crystal; if the DOI information exists, applying the DOI information to image reconstruction; and if the DOI information does not exist, reconstructing the image by using the system response matrix.

Preferably, applying the DOI information to image reconstruction comprises the steps of: layering the crystals by using Gate simulation; obtaining the space coordinates of the accurate deposition positions of the current pair of photons in the crystal by using Gate simulation; obtaining a connecting line of the central coordinates of the layered surfaces of the crystals by using the space coordinates, obtaining two crystals where the intersection points of the connecting line and the surfaces of the crystal arrays are located, and determining the number of the LOR where the connecting line is located by the two crystals, namely obtaining the LOR where the current pair of photons is located; the spatial coordinates of the exact deposition location of the current pair of photons in the crystal are substituted for the photon coordinates in the LOR to reconstruct the image.

Preferably, applying the DOI information to image reconstruction further comprises the steps of: layering different DOI precisions of the crystal under the same set of simulation data by using Gate simulation to obtain a plurality of sets of data after DOI processing with different precisions, and then reconstructing the image of the plurality of sets of data after DOI processing by using the ordered subset maximum expectation algorithm.

Preferably, the method further comprises the steps of: and judging whether the quality of the result of image reconstruction meets the expectation, if not, reducing the average DOI precision of a plurality of groups, increasing the number of groups to obtain optimized data processed by the DOI of the plurality of groups, and reconstructing the image by utilizing the ordered subset maximum expectation algorithm.

Preferably, the system response matrix is generated by using Gate simulation, including acquiring response functions of all positions in the whole image view by using monte carlo simulation, and obtaining the system response matrix according to the response functions of all positions.

A second object of the present invention is to provide an image reconstruction apparatus comprising: an acquisition unit configured to acquire scan data of an imaging target; a judging unit configured to judge whether DOI information exists in the scan data; wherein the DOI information is used to locate the deposition location of the photons in the crystal; a processing unit configured to apply DOI information to image reconstruction if the DOI information is present; and if the DOI information does not exist, reconstructing the image by using the system response matrix.

A third object of the present invention is to provide an image reconstruction apparatus comprising: a memory having program code stored thereon; a processor coupled with the memory and when the program code is executed by the processor, implementing the image reconstruction method described herein.

A fourth object of the present invention is to provide an image reconstruction method, comprising the steps of: acquiring scanning data of an imaging target; judging whether DOI information exists in the scanning data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process; if the DOI information exists, activating a DOI precision reconstruction model in an image reconstruction model library; the image reconstruction model library is at least provided with a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model; waiting and responding to the type of the called reconstruction model in the image reconstruction model library; and constructing the type of reconstruction model by using a simulation system, and then performing image reconstruction by using the reconstruction model.

Preferably, the generating step of the DOI-precision reconstruction model includes: layering the crystals by using Gate simulation; obtaining the space coordinates of the accurate deposition positions of the current pair of photons in the crystal by using Gate simulation; obtaining a connecting line of the central coordinates of the layered surfaces of the crystals by using the space coordinates, obtaining two crystals where the intersection points of the connecting line and the surfaces of the crystal arrays are located, and determining the number of the LOR where the connecting line is located by the two crystals, namely obtaining the LOR where the current pair of photons is located; the spatial coordinates of the exact deposition location of the current pair of photons in the detector are substituted for the photon coordinates in the LOR to reconstruct the image.

Preferably, the generating step of the DOI-precision reconstruction model further includes: layering different DOI precisions of the crystal under the same set of simulation data by using Gate simulation to obtain a plurality of sets of data after DOI processing with different precisions, and then reconstructing the image of the plurality of sets of data after DOI processing by using the ordered subset maximum expectation algorithm.

Preferably, the generating step of the DOI-precision reconstruction model further includes: and judging whether the quality of the result of image reconstruction meets the expectation, if not, improving the average DOI precision of a plurality of groups, increasing the number of the groups to obtain optimized data after the DOI processing of the plurality of groups, and reconstructing the image by utilizing the ordered subset maximum expectation algorithm.

Preferably, the generating step of the monte carlo simulation reconstruction model includes: monte Carlo simulation reconstruction is carried out by using the Gate, response functions of all positions in the whole image visual field are collected, and a system response matrix is obtained according to the response functions of all the positions.

A fifth object of the present invention is to provide an image reconstruction apparatus, comprising: an acquisition unit that acquires scan data of an imaging target; a judging unit configured to judge whether DOI information exists in the scan data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process; a processing unit configured to activate a DOI accuracy reconstruction model in an image reconstruction model library if DOI information exists; waiting and responding to the type of the called reconstruction model in the image reconstruction model library; constructing a reconstruction model of the type by using a simulation system, and then performing image reconstruction by using the reconstruction model; and at least a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model are configured in the image reconstruction model library.

A sixth object of the present invention is to provide an image reconstruction apparatus comprising: a memory having program code stored thereon; a processor coupled with the memory and when the program code is executed by the processor, implementing the image reconstruction method described herein.

A seventh object of the present invention is to provide an image generating method including the image reconstructing method.

An eighth object of the present invention is to provide a computer-readable storage medium having stored thereon program instructions that, when executed, implement the image generation method described herein.

A ninth object of the present invention is to provide an imaging system comprising: an image reconstruction device; and the detector is connected with the image reconstruction device.

Preferably, the detector comprises a PET detector, a PET-CT detector, a PET-MR detector or an MR detector.

Compared with the prior art, the invention has the beneficial effects that: the invention provides an image reconstruction method, which is used for constructing image reconstruction algorithm supports facing different demand scenes by utilizing DOI information, so that reconstructed images meeting different demands are obtained, and the problem of retraction during image reconstruction is solved.

The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:

FIG. 1 is a schematic diagram of the parallax effect of a PET image as an example;

fig. 2 is a schematic flowchart of an image reconstruction method according to embodiment 1;

FIG. 3 is a first flowchart illustrating DOI accuracy reconstruction according to the image reconstruction method of the present invention;

FIGS. 4a-4d are projection views after different DOI depth processing with x-y plane lattice column data in accordance with the present invention;

FIG. 5 is a second flowchart illustrating DOI accuracy reconstruction according to the image reconstruction method of the present invention;

FIGS. 6a-6d are image diagrams obtained by performing different DOI depth simulation reconstructions using a ring according to the present invention;

FIGS. 7a-7c are image diagrams obtained by DOI and Monte Carlo simulation reconstruction using a circular ring in accordance with the present invention;

FIGS. 8a and 8b are images obtained by DOI reconstruction using rings and polygons according to the present invention;

FIGS. 9a-9b are image diagrams obtained using a circular ring for low count DOI and Monte Carlo simulation reconstruction in accordance with the present invention;

FIG. 9c is a plot of image center connections obtained using a low count DOI with a circular ring and Monte Carlo simulation reconstruction in accordance with the present invention;

FIG. 10 is a schematic view of an image reconstructing apparatus according to embodiment 2;

FIG. 11 is a schematic view of an image reconstructing apparatus according to embodiment 3;

fig. 12 is a flowchart illustrating an image reconstruction method according to embodiment 4;

FIG. 13 is a schematic view of an image reconstructing apparatus according to embodiment 5;

FIG. 14 is a schematic view of an image reconstructing apparatus according to embodiment 6;

fig. 15 is a schematic view of an image imaging system in embodiment 8.

Detailed Description

The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.

In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.

The image reconstruction method provided by the application can be applied to various high-energy photon imaging systems, for example, a PET imaging system, a Computed Tomography (CT) imaging system, a PET-CT imaging system, a Magnetic Resonance (MR) imaging system, a PET-MR imaging system, and an application environment in which image reconstruction is performed after data acquisition by various detectors, because corresponding crystals are required to be adopted in the imaging systems to deposit high-energy photons (such as X-rays, gamma rays, neutron rays, and the like), the high-energy photons are finally converted into electric signals to be output, and the high-energy photons all have corresponding DOI information in the corresponding crystals. In particular, in a PET system, the detector may include a plurality of probes, two probes detecting a coincidence event may constitute a probe pair, and one or more lines of response may be formed on each probe pair.

As shown in fig. 1, the parallax effect may cause the reconstructed object to shrink toward the center, resulting in deviation of the reconstruction result, and the present invention aims to solve this problem to obtain a more accurate reconstructed image. There are two main ways to solve this problem: 1. and the DOI detector is adopted to obtain DOI information, so that the deposition position of photons in the crystal is more accurately positioned, and the DOI information is applied to reconstruction to obtain an accurate reconstructed image. 2. A more accurate System Response Matrix (SRM) is used. Both of the above-mentioned methods can correct the image shrinkage, but both methods have a short plate to which they are applied, which is one of the problems that the invention is intended to solve.

Example 1

Referring to fig. 2, the image reconstruction method provided by the present invention includes the following steps:

s11, acquiring scanning data of the imaging target;

s12, judging whether the DOI information exists in the scanning data;

s13, if the DOI information exists, applying the DOI information to image reconstruction;

and S14, if the DOI information does not exist, reconstructing the image by using the system response matrix.

In the present embodiment, when a DOI detector is configured in a system (such as a PET system) for scanning an imaging target, relevant DOI information is obtained from the scanning data, wherein the DOI information is used to locate the deposition position of photons in the crystal; layering the detector according to DOI information to obtain a layer of photons specifically deposited in the detector, solving an intersection point between a layered central connecting line and the surface of the detector to obtain more accurate data and eliminate the positioning error of the LOR, and then calculating by utilizing a Ray-tracing algorithm to obtain a geometric projection matrix G which is used as a system response matrix to obtain a better reconstructed image.

As shown in fig. 3, in a preferred embodiment, applying the DOI information to PET image reconstruction comprises the steps of:

s131, layering the crystals of the PET detector by using Gate simulation;

s132, obtaining the space coordinates of the accurate deposition positions of the current pair of photons in the crystal by using Gate simulation;

s133, obtaining a connecting line of the central coordinates of the layered surfaces of the crystals by using the space coordinates, obtaining two crystals where the intersection points of the connecting line and the surfaces of the crystal arrays are located, and determining the number of the LOR where the two crystals are located by the two crystals, namely obtaining the LOR where the current pair of photons are located;

and S134, replacing the space coordinates of the accurate deposition positions of the current pair of photons in the crystal with the photon coordinates in the LOR to reconstruct an image.

In this embodiment, the simulation is implemented based on Gate simulation, wherein the simulation prosthesis used is an x-y plane point source array, and the pixel source size is 2 × 2 × 2mm using Voxelized simulation³The interval between adjacent points is 6 mm; the x, y coordinates both start at the 4 th pixel's center coordinate and increment by 6mm to the 130 th pixel's center coordinate.

As shown in fig. 4a-4d, some regular gaps appear in the DOI processed projection data (sinogram data), and as the DOI depth increases (where fig. 4a is the original projection data of x-y plane lattice column data, fig. 4b is the projection data with the DOI depth of 2mm, fig. 4c is the projection data with the DOI depth of 4mm, and fig. 4d is the projection data with the DOI depth of 10 mm), the gaps become more obvious, which is caused by the decrease of DOI precision, so that the accuracy of spatial point positioning decreases, and the data is more discrete.

It should be noted that the DOI depth represents the minimum unit of the acquired photon position, that is, the larger the DOI depth, the lower the DOI precision, and there should not be any technical understandings and technical solutions unclear.

It should be understood that the reduction of DOI precision refers to the improvement of DOI resolution, and conversely, the reduction of DOI resolution may result in the degradation of the quality of the reconstructed image, with higher DOI resolution being better. In the limit, the optimal resolution is 0, i.e. the exact deposition location of each photon is known.

In another preferred embodiment, as shown in fig. 5, applying said DOI information to PET image reconstruction comprises the steps of:

s135, layering the crystals of the PET detector with different DOI precisions under the same set of simulation data by using Gate simulation;

s136, obtaining a space coordinate set of accurate deposition positions of a pair of photons under the same set of simulation data under different DOI (direction of arrival) precision conditions by utilizing Gate simulation;

s137, obtaining two crystals where the intersection point of the connecting line of the central coordinates of the layered surfaces of the crystals and the surface of the crystal array is located by utilizing the space coordinate set, and determining the LOR set where the two crystals are located, namely obtaining the LOR set where a plurality of sets of DOI-processed photons with different precisions are located;

s138, carrying out image reconstruction on the data (the space coordinate group and the LOR group where the photons are located) after the DOI processing by utilizing Ordered Subsets (OSEM for short) for maximum Expectation.

As shown in fig. 6a-6d, the simulated prosthesis is a concentric ring, and is an image map obtained by performing simulation reconstruction of different DOI depths based on Gate simulation; the prosthesis is placed in the center of the probe, the ring width is 5mm, the outer radius of the ring is 20mm to 60mm, the interval between adjacent rings is 5mm, and the ring height is 150 mm. As can be seen from the results in the figure, when reconstruction is performed by using the original deposition position (fig. 6a, equivalent DOI resolution is 0, and the deposition position of each photon can be accurately located), as DOI precision becomes higher (DOI resolution is 2 in fig. 6b, DOI resolution is 4 in fig. 6c, and DOI resolution is 10 in fig. 6 d), inaccurate positioning occurs, and thus the recovery effect on the position offset is reduced.

Since the results obtained by DOIs with different accuracies are different (see fig. 4a to 4c), but selecting too high DOI resolution results in a geometric increase of the simulation data amount, the image reconstruction method may further include the steps of:

s139, judging whether the quality of the image reconstruction result meets the expectation;

s1391, if the DOI does not meet the expectation, reducing the average DOI precision of a plurality of groups, increasing the number of the groups, carrying out simulation again to obtain optimized data after the DOI processing of the plurality of groups, and then carrying out image reconstruction by utilizing the ordered subset maximum expectation algorithm;

and S1392, if the image is in accordance with the expectation, outputting the current image reconstruction result.

In this embodiment, when a DOI detector does not exist in the PET system, DOI information cannot be generated after scanning an imaging target, at this time, the PET system needs to construct a system response matrix in other ways, and specifically, the actual PET system may be used to acquire point source imaging data at different positions in the entire image Field of View (Field of View, abbreviated as FOV), and a system response matrix is obtained by fitting according to the data; preferably, the system response matrix can also be generated by using Gate simulation, namely Monte Carlo simulation reconstruction: the method comprises the steps of utilizing Monte Carlo simulation to collect response functions of all positions in the whole image view, and obtaining a system response matrix according to the response functions of all the positions.

It should be understood that, since the number of points in the FOV is large and the calculation workload for each position is large, when the above two methods are used for calculation, the system symmetry is analyzed, the system responses of all voxels in a part of the area in the FOV are calculated, and then the system responses of all positions in the FOV are obtained through the symmetry calculation, and finally, a complete system response matrix is obtained.

In another specific embodiment, based on Gate simulation, wherein the simulated prosthesis is concentric rings; the prosthesis is placed in the center of the probe, the ring width is 5mm, the outer radius of the ring is 20mm to 60mm, the interval between adjacent rings is 5mm, and the ring height is 150 mm.

As shown in fig. 7a-7c, it can be seen from the results in the figures that, due to the effect of the parallax effect, the reconstruction result (fig. 7a) obtained without any correction shrinks inward, and the "shrinking" problem can be effectively solved when the reconstruction is performed by using resolution modeling (fig. 7b) or the reconstruction is performed by adding the original deposition position (fig. 7c can be equivalent to 0 DOI resolution, and can be accurately positioned to the deposition position of each photon), and the reconstruction performed by using two resolution modeling and the DOI reconstruction performed by adding the original deposition position can both obtain better effects.

As shown in fig. 8a and 8b, the data processing can determine the intersection of the LOR with the detector using two calculations:

1. the detection system is approximated as a cylinder and the intersection point is calculated (fig. 8 a);

2. the intersection point is calculated for the detection system as a polygon approximation (fig. 8 b).

The results in the figure show that the position can be well recovered after DOI treatment, and the difference between the two shapes of the detector is not large because the brain PET system consists of 44 detection plates and the shape is close to a cylinder.

As shown in fig. 9a to 9c, it can be seen from the above results that at the time of low count, there is almost no difference between the results of performing the resolution modeling reconstruction and performing the DOI precision reconstruction (raw deposition position), and both have a good correction effect on the difference response.

It should be understood that, in this embodiment, through the judgment of the DOI information, a corresponding system response matrix is automatically constructed, the selection process of the reconstruction model is simplified, and meanwhile, advantages of each reconstruction model are compared, so as to provide a theoretical basis and implementation guidance for recommending a corresponding reconstruction model according to an actual scene.

Example 2

As shown in fig. 10, there is provided an image reconstruction apparatus 100 including: an acquisition unit 101, a judgment unit 102 and a processing unit 103; wherein the content of the first and second substances,

an acquisition unit 101 configured to acquire scan data of an imaging target; a judging unit 102 configured to judge whether DOI information exists in the scan data; wherein the DOI information is used to locate the deposition location of the photons in the crystal; a processing unit 103 configured to apply DOI information to image reconstruction if present; and if the DOI information does not exist, reconstructing the image by using the system response matrix.

For the detailed description of each unit, reference may be made to the corresponding description in the above method embodiment, and details are not repeated here.

In an embodiment, the image reconstruction apparatus 100 further includes a reconstruction model library, in which at least a DOI precision reconstruction model and a monte carlo simulation reconstruction model are configured. And establishing a corresponding system response matrix through a reconstruction model in a reconstruction model library so as to reconstruct the scanning data and correct the image retraction.

It should be understood that the reconstruction model library may be configured in other devices in communication with the image reconstruction device 100, and that the present application may be implemented by accessing or invoking the reconstruction models of the reconstruction model library via communication.

Example 3

Referring to fig. 11 and 15, the image reconstruction apparatus 200 is embodied in the form of a general purpose computing device; including but not limited to: a memory 201, a processor 202; wherein the content of the first and second substances,

a memory 201 having program code stored thereon; a processor 202 coupled with the memory and implementing the image reconstruction method of embodiment 1 when the program code is executed by the processor.

The PET image reconstruction device 200 may further include a bus 600 connecting the various system components including the memory 201 and the processor 202, a display unit 700, and the like. Bus 600 may represent one or more of any of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

Example 4

As shown in fig. 12, an image reconstruction method includes the following steps:

s21, acquiring scanning data of the imaging target;

s22, judging whether the DOI information exists in the scanning data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process;

s23, if the DOI information exists, activating a DOI precision reconstruction model in the image reconstruction model library; the image reconstruction model library is at least provided with a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model;

s24, if the DOI information does not exist, shielding the DOI precision reconstruction model in the image reconstruction model base;

s25, waiting and responding the type of the called reconstruction model in the image reconstruction model library;

and S26, constructing the type of reconstruction model by using the simulation system, and then performing image reconstruction by using the reconstruction model.

In the embodiment, when a DOI detector is configured in the scanning system, relevant DOI information can be obtained from the scanning data, wherein the DOI information is used for positioning the deposition position of photons in the crystal; at the moment, activating the DOI precision reconstruction model, and selecting the DOI precision reconstruction model or the Monte Carlo simulation reconstruction model by a user; although the DOI precision reconstruction model can quickly obtain a system response matrix, only the geometric relation is considered, the physical relation is not considered, and the accuracy is not good than that of a Monte Carlo simulation reconstruction model; therefore, for scenes with high image reconstruction quality requirements, a Monte Carlo simulation reconstruction model is recommended, image reconstruction is not required to be executed after a system response matrix is established through a DOI precision reconstruction model, and whether the execution quality judgment and the identification meet expectations or not is judged, so that the simulation time is greatly saved, and the simulation application is practical.

It should be understood that the building processes of the DOI precision reconstruction model and the monte carlo simulation reconstruction model respectively correspond to the image reconstruction method in embodiment 1 in which the DOI detector exists and the DOI detector does not exist, and are not described herein again.

It should be further understood that, in this embodiment, through the judgment of the DOI information, the image reconstruction model library is reconstructed, the selection types of the reconstruction models are enriched, and at the same time, the advantages of each reconstruction model are fully exerted, so that a theoretical basis and an implementation guide are provided for recommending the corresponding reconstruction model according to an actual scene.

Example 5

As shown in fig. 13, an image reconstruction apparatus 300 includes: an acquisition unit 301, a judgment unit 302 and a processing unit 303; wherein the content of the first and second substances,

an acquisition unit 301 that acquires scan data of an imaging target; a judging unit 302 configured to judge whether DOI information exists in the scan data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process; a processing unit 303 configured to activate a DOI precision reconstruction model in the image reconstruction model library if DOI information exists; waiting and responding to the type of the called reconstruction model in the image reconstruction model library; constructing a reconstruction model of the type by using a simulation system, and then performing image reconstruction by using the reconstruction model; and at least a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model are configured in the image reconstruction model library.

In an embodiment, the image reconstruction apparatus 300 further includes a reconstruction model library, in which at least a DOI precision reconstruction model and a monte carlo simulation reconstruction model are configured. And establishing a corresponding system response matrix through a reconstruction model in a reconstruction model library so as to reconstruct the data scanned by the PET system and correct the image retraction.

It should be understood that the reconstruction model library may be configured in other devices in communication with the image reconstruction device 300, and that the present application may be implemented by accessing or invoking the reconstruction models of the reconstruction model library via communication.

Example 6

Referring to fig. 14 and 15, an image reconstruction apparatus 400 in the form of a general purpose computing device is shown; including but not limited to: a memory 401, a processor 402; wherein the content of the first and second substances,

a memory 401 having program code stored thereon; a processor 402 coupled with the memory and implementing the image reconstruction method of embodiment 4 when the program code is executed by the processor.

The image reconstruction device 400 may also include a bus 600, a display unit 700, etc. connecting the various system components, including the memory 401 and the processor 402. Bus 600 may represent one or more of any of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

Example 7

An image generation method including the image reconstruction method described in embodiment 1 or embodiment 4. By utilizing the method, different image reconstruction algorithms are provided for users with different requirements, so that expected reconstructed images under different requirements are obtained, and the problem of retraction of the reconstructed images is solved.

Example 8

As shown in fig. 15, an imaging system includes: an image reconstruction device; and a detector 500 connected to the image reconstruction device. The image reconstruction device may include the image reconstruction devices in embodiments 2, 3, 5, and 6; the detectors may include PET detectors, PET-CT detectors, PET-MR detectors, or the like. For a detailed description of these probes reference can be made to the prior art and will not be described in any further detail here.

Example 9

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. The technical solution according to the embodiments of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several computer program instructions to make a computing device (which may be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the embodiments of the present application.

The number of apparatuses and the scale of the process described herein are intended to simplify the description of the present invention. Applications, modifications and variations of the present invention will be apparent to those skilled in the art.

While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.

The apparatus, the electronic device, the nonvolatile computer storage medium and the method provided in the embodiments of the present description correspond to each other, and therefore, the apparatus, the electronic device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.

As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The foregoing is illustrative of embodiments of the present disclosure and is not intended to limit one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of the present specification should be included in the scope of claims of one or more embodiments of the present specification. One or more embodiments of this specification.

Claims

1. An image reconstruction method, comprising the steps of:

acquiring scanning data of an imaging target;

judging whether DOI information exists in the scanning data; wherein the DOI information is used to locate the deposition location of the photons in the crystal;

if the DOI information exists, applying the DOI information to image reconstruction;

and if the DOI information does not exist, reconstructing the image by using the system response matrix.

2. The image reconstruction method according to claim 1, wherein applying the DOI information to image reconstruction comprises the steps of:

layering the crystals by using Gate simulation;

obtaining the space coordinates of the accurate deposition positions of the current pair of photons in the crystal by using Gate simulation;

obtaining a connecting line of the central coordinates of the layered surfaces of the crystals by using the space coordinates, obtaining two crystals where the intersection points of the connecting line and the surfaces of the crystal arrays are located, and determining the number of the LOR where the connecting line is located by the two crystals where the connecting line is located to obtain the LOR where the current pair of photons are located;

the spatial coordinates of the exact deposition location of the current pair of photons in the crystal are substituted for the photon coordinates in the LOR to reconstruct the image.

3. The image reconstruction method according to claim 2, wherein applying the DOI information to image reconstruction further comprises the steps of:

layering different DOI precisions of the crystal under the same set of simulation data by using Gate simulation to obtain a plurality of sets of data after DOI processing with different precisions, and then reconstructing the image of the plurality of sets of data after DOI processing by using the ordered subset maximum expectation algorithm.

4. The image reconstruction method according to claim 3, further comprising the steps of:

and judging whether the quality of the result of image reconstruction meets the expectation, if not, reducing the average DOI precision of a plurality of groups, increasing the number of groups to obtain optimized data processed by the DOI of the plurality of groups, and reconstructing the image by utilizing the ordered subset maximum expectation algorithm.

5. The image reconstruction method of claim 1, wherein the system response matrix is generated by using Gate simulation, and the method comprises acquiring response functions of all positions in the whole image field of view by using monte carlo simulation, and obtaining the system response matrix according to the response functions of all positions.

6. An image reconstruction apparatus, comprising:

an acquisition unit configured to acquire scan data of an imaging target;

a judging unit configured to judge whether DOI information exists in the scan data; wherein the DOI information is used to locate the deposition location of the photons in the crystal;

a processing unit configured to apply DOI information to image reconstruction if the DOI information is present; and if the DOI information does not exist, reconstructing the image by using the system response matrix.

7. An image reconstruction apparatus, comprising: a memory having program code stored thereon; a processor coupled with the memory and implementing the method of any of claims 1 to 5 when the program code is executed by the processor.

8. An image reconstruction method, comprising the steps of:

acquiring scanning data of an imaging target;

judging whether DOI information exists in the scanning data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process;

if the DOI information exists, activating a DOI precision reconstruction model in an image reconstruction model library; the image reconstruction model library is at least provided with a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model;

waiting and responding to the type of the called reconstruction model in the image reconstruction model library;

and constructing the type of reconstruction model by using a simulation system, and then performing image reconstruction by using the reconstruction model.

9. The image reconstruction method according to claim 8, wherein the generating of the DOI-accurate reconstruction model includes:

layering the crystals by using Gate simulation;

obtaining a connecting line of the central coordinates of the layered surfaces of the crystals by using the space coordinates, obtaining two crystals where the intersection points of the connecting line and the surfaces of the crystal arrays are located, and determining the number of the LOR where the connecting line is located by the two crystals, so as to obtain the LOR where the current pair of photons is located;

the spatial coordinates of the exact deposition location of the current pair of photons in the detector are substituted for the photon coordinates in the LOR to reconstruct the image.

10. The image reconstruction method according to claim 9, wherein the generating of the DOI-accurate reconstruction model further comprises: layering different DOI precisions of the crystal under the same set of simulation data by using Gate simulation to obtain a plurality of sets of data after DOI processing with different precisions, and then reconstructing the image of the plurality of sets of data after DOI processing by using the ordered subset maximum expectation algorithm.

11. The image reconstruction method according to claim 10, wherein the generating of the DOI-accurate reconstruction model further comprises: and judging whether the quality of the result of image reconstruction meets the expectation, if not, improving the average DOI precision of a plurality of groups, increasing the number of the groups to obtain optimized data after the DOI processing of the plurality of groups, and reconstructing the image by utilizing the ordered subset maximum expectation algorithm.

12. The image reconstruction method according to claim 8, wherein the generating of the Monte Carlo simulation reconstruction model comprises: monte Carlo simulation reconstruction is carried out by using the Gate, response functions of all positions in the whole image visual field are collected, and a system response matrix is obtained according to the response functions of all the positions.

13. An image reconstruction apparatus, comprising:

an acquisition unit that acquires scan data of an imaging target;

a judging unit configured to judge whether DOI information exists in the scan data; the DOI information at least comprises a deposition position of a positioning photon in the crystal, and the DOI information is used for configuring and generating a DOI precision reconstruction model in the simulation process;

a processing unit configured to activate a DOI accuracy reconstruction model in an image reconstruction model library if DOI information exists; waiting and responding to the type of the called reconstruction model in the image reconstruction model library; constructing a reconstruction model of the type by using a simulation system, and then performing image reconstruction by using the reconstruction model; and at least a DOI precision reconstruction model and a Monte Carlo simulation reconstruction model are configured in the image reconstruction model library.

14. An image reconstruction apparatus, comprising: a memory having program code stored thereon; a processor coupled with the memory and implementing the method of any of claims 8 to 12 when the program code is executed by the processor.

15. An image generation method comprising the image reconstruction method of any one of claims 1 to 5 or 8 to 12.

16. A computer-readable storage medium having stored thereon program instructions that, when executed, implement the PET image generation method of claim 15.

17. An imaging system, comprising: the image reconstruction apparatus of any one of claims 6-7 or 13-14; and the detector is connected with the image reconstruction device.

18. The imaging system of claim 17, wherein the detector comprises a PET detector, a PET-CT detector, a PET-MR detector, or an MR detector.