CN113397581B - Method and device for reconstructing medical dynamic image - Google Patents
Method and device for reconstructing medical dynamic image Download PDFInfo
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Abstract
The invention provides a method for reconstructing a medical dynamic image, which comprises the following steps: extracting an interested region of a medical dynamic image, wherein the medical dynamic image comprises images of a human body part shot in a plurality of time intervals; acquiring a curve of the activity of the radiopharmaceutical injected into the region of interest along with the change of time; determining an interesting time period according to the curve, wherein the interesting time period comprises the moment of the maximum value of the activity; and reconstructing an image of the region of interest in the interested period according to the activity change of the pixels of the region of interest. According to the technical scheme of the invention, the dynamic image is analyzed, and the image of the region of interest in the time period most suitable for observation is reconstructed, so that a reader can visually see the signal intensity change condition of the region of interest.
Description
Technical Field
The present invention relates to the field of medical imaging, and more particularly, to a method and apparatus for reconstructing a medical dynamic image.
Background
Nuclear medicine is an emerging discipline that employs nuclear technology to diagnose, treat, and study disease, including clinical and basic nuclear medicine. Nuclear medicine imaging technology has made breakthrough progress since the 70 s due to the development of single photon Emission Computed Tomography (PET) technology, and the innovation and development of radiopharmaceuticals. It complements and verifies with CT, nuclear magnetic resonance, ultrasonic technology and the like, and greatly improves the diagnosis and research level of diseases, so nuclear medicine imaging is a very active branch and an important component in the field of recent clinical medical image diagnosis.
In the course of clinical trials of new drugs, it is necessary to label them with isotopes in order to investigate various problems of drug metabolism, for example, in order to determine the active metabolites of drugs and to evaluate their pharmacological effects. For example, the metabolic status of a tracer drug in an organ of an animal can be followed by medical imaging.
However, the current image acquisition method has difficulty in ensuring that the acquisition time window is just the period of time when the tracer drug metabolism of the region of interest is most vigorous.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method and an apparatus for reconstructing a medical dynamic image.
In a first aspect, an embodiment of the present invention provides a method for reconstructing a medical dynamic image, including: extracting an interested region of a medical dynamic image, wherein the medical dynamic image comprises images of a human body part shot in a plurality of time intervals; acquiring a curve of the activity of the radiopharmaceutical injected into the region of interest along with the change of time; determining an interesting time period according to the curve, wherein the interesting time period comprises the moment of the maximum value of the activity; and reconstructing an image of the region of interest in the interested period according to the activity change of the pixels of the region of interest.
In some embodiments of the invention, obtaining a time-dependent profile of activity of the radiopharmaceutical injected into the region of interest comprises: establishing a dynamic equation based on an atrioventricular model of the region of interest, wherein the atrioventricular model comprises a central chamber and peripheral chambers, and the dynamic equation comprises an equation of the change of the drug activity of the central chamber along with time and an equation of the change of the drug activity of the peripheral chambers along with time; determining a proportionality coefficient between an equation of time-varying drug activity in the central chamber and an equation of time-varying drug activity in the peripheral chambers; and determining a curve according to a kinetic equation and a proportionality coefficient.
In some embodiments of the invention, the curve is determined by the following equation: creal(T)=k1C1real(T)+k2C2real(T) wherein Creal(T) Activity of the region of interest at time T, C1real(T) drug activity of the central compartment at time T, C2real(T) drug activity in the peripheral compartment at time T, k1Is the proportionality coefficient, k, of the equation relating the activity of the drug in the central compartment to the time2Proportionality coefficient, k, of equation of time-dependent change in drug activity in the peripheral compartment1And k2Satisfy k1+k2=1。
In some embodiments of the invention, determining the period of interest from the curve comprises: presetting an activity threshold according to the maximum value of the activity; the period of interest is determined from the maximum value of the activity and the activity threshold.
In some embodiments of the invention, determining the period of interest based on the maximum value of the activity and the activity threshold comprises: and determining a first time and a second time when the activity value on the curve is equal to the activity threshold value, wherein the first time is less than the second time, and the interested time period is from the first time to the second time.
In some embodiments of the invention, determining the period of interest from the curve comprises: determining the slope of a rising edge and the slope of a falling edge of the curve; the period of interest is determined based on the maximum value of the activity, the slope of the rising edge and the slope of the falling edge.
In a second aspect, an embodiment of the present invention provides an apparatus for reconstructing a medical dynamic image, including: the extraction module is used for extracting an interested region of a medical dynamic image, and the medical dynamic image comprises images of a human body part shot in a plurality of time intervals; the acquisition module is used for acquiring a curve of the change of the activity of the injected radiopharmaceutical in the region of interest along with time; a determining module, configured to determine, according to the curve, a time period of interest, where the time period of interest includes a time at which a maximum value of the activity is located; and the reconstruction module is used for reconstructing an image of the interested region in the interested time period according to the activity change of the pixels of the interested region.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program for executing the method for reconstructing a medical dynamic image according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides an electronic device, including: a processor; a memory for storing processor executable instructions, wherein the processor is adapted to perform the method of reconstructing a medical dynamic image of the first aspect.
According to the technical scheme of the invention, the dynamic image is analyzed, and the image of the region of interest in the time period most suitable for observation is reconstructed, so that a reader can visually see the signal intensity change condition of the region of interest.
Drawings
Fig. 1 is a schematic diagram of an implementation environment for reconstructing a medical dynamic image according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating a method for reconstructing a medical dynamic image according to an embodiment of the present invention.
Fig. 3 is a schematic flowchart of calculating an activity curve of a region of interest according to another embodiment of the present invention.
Fig. 4 is a flowchart illustrating a process of determining a period of interest according to another embodiment of the present invention.
Fig. 5 is a flowchart illustrating a process of determining a period of interest according to another embodiment of the present invention.
Fig. 6a is a schematic diagram illustrating a comparison of single and multiple PET image acquisition processes according to an exemplary embodiment of the present invention.
FIG. 6b is a schematic view of a two component compartmental model according to an exemplary embodiment of the present invention.
Fig. 6c is a schematic diagram illustrating comparison of an activity curve of a region of interest with an observed value and reconstruction of the region of interest according to an exemplary embodiment of the present invention.
Fig. 7 is a schematic structural diagram of an apparatus for reconstructing a medical dynamic image according to another embodiment of the present invention.
Fig. 8 is a block diagram of an electronic device for executing a method of reconstructing a medical dynamic image according to an exemplary embodiment of the present invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
The term "include" and variations thereof as used herein are intended to be open-ended, i.e., "including but not limited to". The term "according to" is "at least partially according to". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment". Relevant definitions for other terms will be given in the following description.
PET (Positron Emission Computed Tomography) is a relatively advanced clinical examination imaging technology in the field of nuclear medicine, and the method is as follows: after the substances (such as glucose, protein, nucleic acid and fatty acid) necessary for biological life metabolism are labeled with short-lived radioactive nuclide and injected into human body, the condition of life metabolic activity can be reflected by the aggregation degree of said substances in metabolism so as to attain the goal of diagnosis.
The radionuclide commonly used in PET is FDG-18 (fluorodeoxyglucose, the fluorine in the molecule being selected from positron-emitting radioisotopes)18F, FDG-18 for short), the mechanism is as follows: the metabolic states of different tissues of a human body are different, glucose metabolism is vigorous and more glucose is accumulated in high-metabolic malignant tumor tissues, and the characteristics can be reflected through images, so that the pathological changes can be diagnosed and analyzed.
For example, PET imaging can be used to assess the activity of tumors by the intensity of uptake of injected radionuclide drugs by the tumor. In this process, in order to reduce the damage to the body of the subject caused by injection, the shorter half-life FDG-18 is often used as a tracer drug for PET imaging.
In the acquisition process of PET images, on one hand, since the tracer generally enters the body of the subject by injection, it takes a certain time for the tracer to diffuse from the injection site to the whole body, and the signal intensity of the acquired images needs to be gradually strengthened after waiting for a certain time after the injection is completed. On the other hand, however, the signal intensity of the acquired image decreases with the decay of the tracer, requiring the subject to acquire the image as soon as possible after the injection is completed.
From the above two points, it can be seen that an optimal time period in which the tracer is stably distributed needs to be found for image signal acquisition. Due to the difference of human body metabolism and drug transport capacity and the difference of drug absorption capacity of the region of interest, it is difficult to ensure that the time window for collection is just the most suitable time window for observation of the region of interest in the actual collection process.
Fig. 6a is a schematic diagram illustrating a comparison of single and multiple PET image acquisition processes according to an exemplary embodiment of the present invention. As can be seen in connection with section a of fig. 6a, it is difficult for a single PET image acquisition to ensure that the time window of acquisition is just the period of most vigorous tracer drug metabolism in the region of interest, especially for patients without prior PET recordings. Therefore, multiple PET image acquisitions of the B-part (i.e. dynamic PET image acquisitions) are often employed to show as many PET images of the drug metabolic processes in the region of interest as possible. However, dynamic PET image acquisition may also suffer from the same problems, e.g. the periods of maximum metabolism of the tracer drug in the region of interest may intersect two consecutive time windows, or span more than two time windows, or only occupy a small part of a certain time window. These conditions all lead to poor visualization of dynamic PET images, i.e. it is difficult to ensure that the time window of acquisition is exactly the period of time in which the tracer drug metabolism in the region of interest is most vigorous.
In order to solve the above problems, the present invention provides a method of reconstructing a medical image.
FIG. 1 is a schematic diagram of an implementation environment provided by an embodiment of the invention. The implementation environment includes a PET acquisition device 110 and a computer device 120.
The computer device 120 may acquire medical motion images from the PET acquisition device 110. For example, the computer device 120 may communicate with the PET acquisition device 110 over a wired or wireless network.
The PET collecting device 110 is used for collecting the signal intensity of the injected radioactive tracer to obtain the PET medical dynamic image of the human body part. In one embodiment, the PET acquisition device 110 acquires the brain of the human body, and a PET medical dynamic image of the brain can be obtained.
The computer device 120 may be a general-purpose computer or a computer device composed of an application-specific integrated circuit, and the like, which is not limited in the embodiment of the present invention. For example, the Computer device 120 may be a mobile terminal device such as a tablet Computer, or may be a Personal Computer (PC), such as a laptop portable Computer and a desktop Computer.
One skilled in the art will appreciate that the number of computer devices 120 described above may be one or more, and that the types may be the same or different. For example, the number of the computer devices 120 may be one, or the number of the computer devices 120 may be several tens or hundreds, or more. The number and types of the computer devices 120 are not limited in the embodiments of the present invention.
In some optional embodiments, the computer device 120 extracts a region of interest of a PET medical motion image from the PET acquisition device 110, the PET medical motion image including images of a human body part taken at a plurality of time intervals, calculates a curve of activity change over time of the radiopharmaceutical injected into the region of interest, determines a time interval of interest from the curve, the time interval of interest including a time at which a maximum value of the activity is located, and reconstructs an image of the region of interest within the time interval of interest from activity change of pixels of the region of interest.
Fig. 2 schematically shows a flowchart of a method for reconstructing a medical dynamic image according to an embodiment of the present invention. The method of fig. 2 is performed by a computing device (e.g., a server or the computer device of fig. 1), but the embodiments of the invention are not limited thereto. The server may be one server, or may be composed of several servers, or may be a virtualization platform, or a cloud computing service center, which is not limited in the embodiment of the present invention. As shown in fig. 2, the method includes the following.
S210: a region of interest of a medical dynamic image is extracted, the medical dynamic image including images of a human body part taken at a plurality of time periods.
In particular, the medical motion image may be a PET medical motion image. For example, a radiotracer drug may be injected into a body part and a PET medical dynamic image of the body part may be taken. For example, embodiments of the present invention may employ FDG-18 as the radiotracer. Because the half-life of the FDG-18 radioactive tracer drug is 6586.2 seconds, and the distribution concentration of the drug is combined, the time period of each image acquisition can be 5min, 6min, 8min, 10min, 12min, 15min and 20min in sequence. The duration and the number of times of the image capturing period can be increased or decreased properly, and 5 to 8 medical images can be captured. It should be understood that the medical dynamic image of the embodiment of the present invention is not limited to the PET medical dynamic image, but may be other nuclear medicine images.
In an embodiment, a user may select a certain region as the interested area on the user interface by using a selection box, for example, the user may select a certain region of interest of one frame of image in the medical dynamic image, and the computer device may extract an image of the corresponding region of interest in each frame of medical image in the medical dynamic image accordingly. For example, the PET acquisition device 110 acquires a brain of a human body to obtain a PET medical dynamic image of the brain, and a certain region on the PET medical dynamic image of the brain is used as a region of interest.
S220: a curve of the activity of the radiopharmaceutical injected in the region of interest as a function of time is acquired.
In one embodiment, a two-component compartmental model (i.e., kinetic two-component model) may be used to calculate a time-dependent curve of the activity of the radiopharmaceutical injected into the region of interest. FIG. 6b is a schematic view of a two component compartmental model according to an exemplary embodiment of the present invention. As shown in FIG. 6b, the two-component compartmental model consists of a plasma chamber, a central chamber and a peripheral chamber, which may also be referred to collectively as the peripheral chamber, which may also be referred to as the isolation chamber or the peripheral chamber, wherein A1Represents the central compartment, A2Represents an isolation chamber, AGIRepresenting the concentration of the tracer drug in the plasma compartment, the variance can be calculated from the above model as:
wherein k isaThe rate of uptake of the tracer drug into the central compartment, also known as the first order rate constant, k12And k21The transfer rates, k, between the central and peripheral chambers, respectively10Is the discharge rate of the central chamber, ka、k12、k21And k10Collectively referred to as pharmacokinetic parameters, C1(t) and C2(t) the concentration of the drug is tracked in the central and peripheral chambers, respectively, at time t. Integrating the above equation then has:
wherein, V1And V2The volumes of the central and peripheral chambers, respectively. In pharmacokinetics, the metabolism of a drug in the body proceeds according to first-order kinetic processes, i.e., the drug also has a relatively stable half-life in the body, and thus needs to be multiplied by a decay factor e-βtObtaining:
C1real(T)=C1(T) e-βt
C2real(T)=C2(T) e-βt
wherein β = (ln2)/T1/2，T1/2Half-life of the radiopharmaceutical, C1real(T) drug activity of the central compartment at time T, C2real(T) drug activity in the peripheral compartment at time T, C1(T) and C2(T) the concentration of the drug is tracked in the central and peripheral chambers, respectively, at time T.
In one embodiment, the time-dependent activity profile of the radiopharmaceutical injected into the region of interest is determined by the following equation:
Creal(T)=k1C1real(T)+ k2C2real(T)
wherein, Creal(T) is the activity of the radiopharmaceutical in the region of interest at time T (i.e. the curve of the activity of the radiopharmaceutical injected in the region of interest as a function of time), C1real(T) drug activity of the central compartment at time T, C2real(T) drug activity in the peripheral compartment at time T, k1Is the proportionality coefficient of the central chamber, k2Is the proportionality coefficient of the peripheral chamber, k1And k2Satisfy k1+k2And =1, namely, the proportion of the central chamber and the peripheral chamber in the region of interest is determined by adopting a linear superposition method.
In fact, any region is not an ideal central or peripheral chamber, and the region of interest can be considered as a superposition of the central and peripheral chambers.
Based on the above formula, the pharmacokinetic parameter k is set according to the initial condition (the first set of images acquired in 5 min) by using least squaresa、k12、k21And k10And setting the above-mentioned proportionality coefficient k1And k2And then, gradually iteratively fitting according to other images, and determining the offset step length of iterative fitting according to a steepest descent method until the images deduced according to the set pharmacokinetic parameter values and the proportionality coefficient values gradually approach to the real images of each group of images (for example, the error is less than 2%), and then considering that the pharmacokinetic parameter values and the proportionality coefficient values obtained by fitting are correct, so as to obtain a curve of the activity of the radiopharmaceutical injected into the region of interest along with the change of time.
In the embodiment, the proportion of the central chamber and the peripheral chambers in the region of interest is determined by adopting a linear superposition method, so that the two-component chamber model has higher theoretical performance and accuracy.
S230: from the curve, a period of interest is determined, which contains the moment at which the maximum of the activity is located.
In one embodiment, determining the period of interest from the curve comprises: presetting an activity threshold according to the maximum value of the activity; the period of interest is determined from the maximum value of the activity and the activity threshold.
Specifically, after a curve of the activity of the radiopharmaceutical injected into the region of interest over time is fitted, 70% of the maximum value of the activity may be set as an activity threshold, and a time period in the curve where the activity is higher than the activity threshold may be set as a time period of interest, so as to further establish an image of a time period most suitable for observation in the region of interest based on the time period of interest. The specific value of the activity threshold may be other values, which is not limited in the present invention.
In an embodiment, determining the period of interest from the maximum of the activities and the activity threshold comprises: and determining a first time and a second time when the activity value on the curve is equal to the activity threshold value, wherein the first time is less than the second time, and the interested time period is from the first time to the second time.
Specifically, after the activity threshold is set, an equation that the activity value on the curve is equal to the activity threshold is established, a first time and a second time are obtained, and the activity value on the curve at the first time or the second time is the activity threshold. The first time may be less than the second time. When more than two moments satisfy the equation, the first moment may be the minimum value thereof, and the second moment may be the maximum value thereof, so as to ensure that the maximum activity value is within the selected period of interest.
In one embodiment, determining the period of interest from the curve comprises: determining the slope of a rising edge and the slope of a falling edge of the curve; the period of interest is determined based on the maximum value of the activity, the slope of the rising edge and the slope of the falling edge.
Specifically, after fitting a curve of the activity of the radiopharmaceutical injected in the region of interest over time, the time period of interest may be determined according to the morphology of the curve, so as to further establish an image of the time period in the region of interest that is most suitable for observation based on the time period of interest. For example, the period of interest on the curve may be determined by calculating the slope of the rising edge and the slope of the falling edge of the curve, and when the slope is greater than a certain value, a shorter period around the maximum value of the activity in the curve is taken as the period of interest, and when the slope is less than a certain value, a longer period around the maximum value of the activity in the curve is taken as the period of interest, so that the reconstructed image of the region of interest within the period of interest has a higher signal-to-noise ratio.
S240: and reconstructing an image of the region of interest in the interested period according to the activity change of the pixels of the region of interest.
Specifically, according to activity variation of pixels of the interested region in the acquired PET image, the image of the interested region in the interested period is reconstructed. For example, an image of the region of interest over the period of interest may be obtained by separately reconstructing the projection data for each time frame. The single-frame reconstruction method may employ an analytical reconstruction method (such as a conventional FBP algorithm) or a statistical iterative reconstruction method, such as a Maximum likelihood estimation-based expectation Maximization (ML-EM) algorithm. The time information can also be introduced into the image reconstruction process in the form of a time basis function, so that the time activity curve of the dynamic image is smoother, and the signal-to-noise ratio of the time activity curve can be improved. In addition, a direct parametric imaging method can also be adopted, and the image of the interested region in the interested period can be directly reconstructed from the projection data by combining the dynamic parameter estimation and the dynamic image reconstruction.
Fig. 6c is a schematic diagram illustrating comparison of an activity curve of a region of interest with an observed value and reconstruction of the region of interest according to an exemplary embodiment of the present invention. As shown in fig. 6c, the fitted curve is very close to the actual observed value, which provides a more intuitive and accurate analysis method for the reader to evaluate the distribution change rule and the transmission capability of the tracer drugs.
In the aspect of engineering implementation, java is used as a development language, for a model fitting part, mathmatic in wolfram is used for implementation, and a model fitting algorithm in wolfram is integrated into a java product by using J/link in workbench in wolfram.
According to the technical scheme of the invention, the dynamic image is analyzed, and the image of the region of interest in the time period most suitable for observation is reconstructed, so that a reader can visually see the signal intensity change condition of the region of interest.
Fig. 3 is a schematic flowchart of a process for calculating an activity curve of a region of interest according to another embodiment of the present invention, including:
s310: and establishing a kinetic equation based on the atrioventricular model, wherein the atrioventricular model comprises a plasma chamber, a central chamber and a peripheral chamber, and the kinetic equation is established based on the atrioventricular model of the region of interest, the atrioventricular model comprises the central chamber and the peripheral chamber, and the kinetic equation comprises an equation of the drug activity of the central chamber changing along with time and an equation of the drug activity of the peripheral chamber changing along with time.
S320: a proportionality coefficient is determined between the equation of time-varying drug activity in the central chamber and the equation of time-varying drug activity in the peripheral chambers.
S330: and determining a curve according to a kinetic equation and a proportionality coefficient.
For specific contents of S310 to S320, reference may be made to the description in the above embodiments, and details are not repeated here to avoid repetition.
Fig. 4 is a schematic flowchart of determining a period of interest according to another embodiment of the present invention, which includes:
s410: the activity threshold is preset according to the maximum value of the activity.
S420: the period of interest is determined from the maximum value of the activity and the activity threshold.
For specific contents of S410 to S420, reference may be made to the description in the above embodiments, and details are not repeated here to avoid repetition.
Fig. 5 is a schematic flowchart of determining a period of interest according to another embodiment of the present invention, which includes:
s510: the slope of the rising edge and the slope of the falling edge of the curve are determined.
S520: the period of interest is determined based on the maximum value of the activity, the slope of the rising edge and the slope of the falling edge.
For specific contents of S510 to S520, reference may be made to the description in the above embodiments, and details are not repeated here to avoid repetition.
Fig. 7 is a schematic structural diagram of an apparatus for reconstructing a medical dynamic image according to another embodiment of the present invention, including:
an extracting module 710, configured to extract a region of interest of a medical dynamic image, where the medical dynamic image includes images of a human body part captured at multiple time intervals;
an obtaining module 720, configured to obtain a time-varying curve of activity of the radiopharmaceutical injected into the region of interest;
the determining module 730 is configured to determine a time period of interest according to the curve, the time period of interest including a time instant at which the maximum value of the activity is located.
And a reconstructing module 740 configured to reconstruct an image of the region of interest in the interested time period according to the activity change of the pixels of the region of interest.
According to the device for reconstructing the medical dynamic image, the dynamic image is analyzed, and the image of the region of interest in the time period most suitable for observation is reconstructed, so that a viewer can visually see the signal intensity change condition of the region of interest.
According to an embodiment of the present invention, the obtaining module 720 establishes a kinetic equation based on an atrioventricular model of the region of interest, the atrioventricular model including a central chamber and a peripheral chamber, the kinetic equation including an equation of a change in drug activity of the central chamber with time and an equation of a change in drug activity of the peripheral chamber with time; determining a proportionality coefficient between an equation of time-varying drug activity in the central chamber and an equation of time-varying drug activity in the peripheral chambers; and determining a curve according to a kinetic equation and a proportionality coefficient.
According to an embodiment of the present invention, the curve of the obtaining module 720 is determined by the following formula: creal(T)=k1C1real(T)+k2C2real(T) wherein Creal(T) Activity of the region of interest at time T, C1real(T) drug activity of the central compartment at time T, C2real(T) drug activity in the peripheral compartment at time T, k1Is the proportionality coefficient, k, of the equation relating the activity of the drug in the central compartment to the time2Proportionality coefficient, k, of equation of time-dependent change in drug activity in the peripheral compartment1And k2Satisfy k1+k2=1。
According to an embodiment of the present invention, the determining module 730 presets an activity threshold according to a maximum value of the activity; the period of interest is determined from the maximum value of the activity and the activity threshold.
According to an embodiment of the present invention, the determining module 730 determines a first time and a second time on the curve where the activity value is equal to the activity threshold, the first time is less than the second time, and the period of interest is from the first time to the second time.
The determination module 730 determines the slope of the rising edge and the slope of the falling edge of the curve, according to an embodiment of the invention; the period of interest is determined based on the maximum value of the activity, the slope of the rising edge and the slope of the falling edge.
For specific limitations of the apparatus for reconstructing a medical dynamic image, reference may be made to the above limitations of the method for reconstructing a medical dynamic image, which are not described herein again.
Fig. 8 is a block diagram of an electronic device for executing a method for reconstructing a medical dynamic image according to an exemplary embodiment of the present application, which includes a processor 810 and a memory 820.
The memory 820 is used to store processor executable instructions. The processor is used for executing the executable instructions to execute the method for reconstructing the medical dynamic image in any one of the above embodiments.
The present application further provides a computer-readable storage medium, which stores a computer program for executing the method for reconstructing a medical dynamic image according to any one of the above embodiments.
The method for reconstructing the medical dynamic image adopts an improved two-component chamber model method, analyzes the dynamic image which is decayed to a certain degree by injecting the tracer agent to the tracer agent, obtains the curve of the activity change of the radiopharmaceutical injected into the region of interest along with the time, determines the most suitable interesting time period for observation in the region of interest according to the maximum value of the activity of the curve, and reconstructs the image of the most suitable time period for observation in the region of interest, so that a reader can visually see the signal intensity change condition of the region of interest.
In the above embodiments, all or part of the implementation may be realized by software, hardware, firmware or any other combination. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. The procedures or functions according to the embodiments of the invention are brought about in whole or in part when the computer program instructions are loaded and executed on a computer. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored on a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server-side, data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a Digital Video Disk (DVD)), or a semiconductor medium (e.g., a Solid State Disk (SSD)), among others.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method for reconstructing a medical motion image, comprising:
extracting a region of interest of a medical dynamic image, wherein the medical dynamic image comprises images of a human body part shot at a plurality of time intervals;
acquiring a curve of the activity of the injected radiopharmaceutical in the region of interest over time;
determining a period of interest from the curve, the period of interest including a time at which a maximum of the activity is located, the period of interest including a plurality of time frames;
reconstructing an image of the region of interest within the period of interest according to activity changes of pixels of the region of interest, wherein the determining the period of interest according to the curve includes:
determining a slope of a rising edge and a slope of a falling edge of the curve;
determining the period of interest from the maximum value of the activity, the slope of the rising edge and the slope of the falling edge, comprising:
determining a first period containing the maximum value as the period of interest when the slope of the rising edge or the slope of the falling edge is greater than a first threshold, and determining a second period containing the maximum value as the period of interest when the slope of the rising edge or the slope of the falling edge is less than the first threshold, wherein the first period is less than the second period.
2. The method of claim 1, wherein said obtaining a time-dependent curve of activity of the radiopharmaceutical injected into the region of interest comprises:
establishing a kinetic equation based on a compartmental model of the region of interest, the compartmental model including a central compartment and a peripheral compartment, the kinetic equation including an equation of change in drug activity over time of the central compartment and an equation of change in drug activity over time of the peripheral compartment;
determining a proportionality coefficient between an equation of time-varying drug activity of the central chamber and an equation of time-varying drug activity of the peripheral chambers;
and determining the curve according to the kinetic equation and the proportionality coefficient.
3. The method of claim 2, wherein the curve is determined by the formula:
Creal(T)=k1C1real(T)+k2C2real(T)，
wherein, Creal(T) the activity of the drug in the region of interest at time T, C1real(T) the drug activity of the central compartment at time T, C2real(T) the drug activity of the peripheral chamber at time T, k1Is the ratio of the equation of the change of the drug activity of the central compartment with timeCoefficient of case, k2Is the proportionality coefficient of the equation of time-dependent change in drug activity of the peripheral chamber, k1And k is said2Satisfy k1+k2=1。
4. The method of claim 1, wherein the medical dynamic image is a dynamic electron emission computed tomography.
5. An apparatus for a method of reconstructing a medical motion image, comprising:
the system comprises an extraction module, a display module and a display module, wherein the extraction module is used for extracting an interested area of a medical dynamic image, and the medical dynamic image comprises images of a human body part shot in a plurality of time intervals;
an acquisition module for acquiring a curve of activity of the radiopharmaceutical injected into the region of interest over time;
a determining module, configured to determine, according to the curve, a time period of interest, where the time period of interest includes a time at which a maximum value of the activity is located, where the time period of interest includes a plurality of time frames, and the determining, according to the curve, the time period of interest includes:
determining a slope of a rising edge and a slope of a falling edge of the curve;
determining the period of interest from the maximum value of the activity, the slope of the rising edge and the slope of the falling edge, comprising:
determining a first period containing the maximum value as the period of interest when the slope of the rising edge or the slope of the falling edge is greater than a first threshold, and determining a second period containing the maximum value as the period of interest when the slope of the rising edge or the slope of the falling edge is less than the first threshold, wherein the first period is less than the second period;
and the reconstruction module is used for reconstructing an image of the region of interest in the interested time period according to the activity change of the pixels of the region of interest.
6. A computer-readable storage medium, in which a computer program is stored, the computer program being adapted to perform the method of reconstructing a medical dynamic image of any one of claims 1 to 4.
7. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions,
wherein the processor is configured to execute the method for reconstructing medical dynamic image as claimed in any one of the above claims 1 to 4.
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