142 results about "Dose calculation" patented technology

The invention discloses a BNCT dose calculation method, which comprises the following steps: S1, constructing a voxel model, initializing one or more particles in a simulation system, and respectively acquiring the initial position, energy and movement direction of each particle; s2, adaptively selecting a Monte Carlo particle tracking algorithm and a flux counting mode based on the region where the particles are located and the energy of the particles; s3, repeating the step S2 until the particles leave the simulation system or are killed when meeting a truncation condition; and S4, cumulatively calculating dose distribution. Through the BNCT dose calculation method, the Monte Carlo particle transport simulation time is greatly shortened, the BNCT dose calculation efficiency is optimized, and the method is suitable for rapid and high-precision radiation dose simulation under a BNCT complex tissue structure.

The invention provides a pencil beam dose calculation method. The pencil beam dose calculation method comprises the following steps: acquiring human body image data; determining a plurality of particle types for treatment; calculating initial pencil beam dose distribution corresponding to each particle type; based on the particle types, target action layers, distributed in the human body image data, of all the doses are determined, and the positions of the target action layers corresponding to different particle types are different; based on the target action layer corresponding to each particle type, adjusting each initial dose distribution, and obtaining particle pencil beam dose distribution corresponding to each particle type; superposing the particle pencil beam dose distribution corresponding to each particle type to obtain target pencil beam dose distribution; wherein the dose proportion of the particle pencil beam dose distribution corresponding to the same particle type in the target action layer is greater than the dose proportion of the particle pencil beam dose of the particle type in other parts in the human body image data.

The invention discloses a radiotherapy dose calculation optimization method and device based on a generative adversarial network, and relates to the technical field of medical plans, and the method comprises the steps: obtaining phase space files and condition vectors of different accelerators, and making a data set; training and verifying the constructed generative adversarial network model by using the data set; determining the value of each parameter in the condition vector according to the actual operation parameter of the specific accelerator, inputting the value to the verified generative adversarial network model, and generating particle distribution data corresponding to the condition vector; and taking particle distribution data generated by the model as initial input of a Monte Carlo (MC) simulation method to obtain a radiotherapy dose distribution result simulated by the MC. Radiotherapy dose calculation is realized through a method of combining the generative adversarial network and MC simulation, and the duration of MC simulation and quality inspection processes can be greatly shortened while the dose calculation precision is ensured.

The invention discloses an alpha nuclide drug in-vitro cellular response prediction method and system based on multi-module mathematical modeling and a medium, and the method comprises the steps: constructing a basic parameter input module, a pharmacokinetic prediction module, a cell absorbed dose calculation module and a biological effect prediction module which are connected in sequence; a three-compartment dynamical model and a micro-dose learning point kernel convolution and DNA damage repair dynamical model are integrated, and full-chain and quantitative simulation from drug distribution, microscopic energy deposition to cell survival is achieved. The method overcomes the defects that an existing empirical model cannot accurately reflect the high LET characteristic of alpha particles, neglects the bystander effect and repair dynamics and the like, and the prediction precision is remarkably improved. According to the method, the curative effects of different drugs, cell lines and dosage schemes can be quickly simulated on a computer, the research and development cost and period are greatly reduced, and an efficient theoretical tool is provided for new drug screening and dosage optimization.

The invention relates to the technical field of radiation environment monitoring, and discloses a dose calculation method and system based on radiation environment monitoring data. The method comprises the following steps: acquiring radiation source data, calculating initial radiation field distribution based on the data, obtaining an initial dose deposition value of each space point in a monitoring area, analyzing interaction among particles, and determining an energy redistribution coefficient of each space point; adjusting the initial dose deposition value point by point by using the coefficient to obtain corrected three-dimensional dose concentration field data, calculating a gradient vector between spatial points, and generating an optimized gradient distribution diagram; extracting a boundary point set with gradient change exceeding a threshold value, constructing a contour surface grid to form a three-dimensional contour surface structure, obtaining a time sequence radiation source data iteration updating coefficient, and obtaining a concentration field time sequence evolution sequence; the high-concentration area is identified and marked based on the sequence, the high-concentration area and the three-dimensional contour surface structure are fused, a visual distribution model reflecting the dose concentration is generated, and the accuracy of radiation dose calculation is improved.

The invention discloses an AI auxiliary radiotherapy dose intelligent optimization device, which comprises a multi-modal image fusion module, a dose distribution prediction module, a dynamic adaptive optimization module and a prognosis model integration module, and is characterized in that the multi-modal image fusion module is used for aligning anatomical features of different images, eliminating respiratory motion artifacts and predicting the dose distribution of the different images; the dose distribution prediction module is used for rapidly predicting radiotherapy dose distribution based on anatomical features and historical data, the dynamic adaptive optimization module is used for monitoring anatomical changes in real time and dynamically adjusting a dose plan, and the prognosis model integration module is used for quantifying correlation between dose distribution and radioactive injury risks. High-precision alignment and respiratory motion artifact elimination of an anatomical structure are achieved through the multi-modal image fusion module, three-dimensional dose calculation is rapidly and accurately conducted through the dose distribution prediction module, organ displacement and deformation are effectively coped with through the dynamic self-adaptive optimization module through a real-time image monitoring and reinforcement learning algorithm, and the accuracy of the three-dimensional dose calculation is improved. And the prognosis model integration module constructs an individualized risk prediction model.

The invention discloses a proton dose information processing device and method and electronic equipment, and relates to the field of medical science and technology. The device comprises a matrix processing unit used for determining a compression matrix according to a physical information table; the particle simulation processing unit is used for simulating the transport behavior of target particles in a medium through a plurality of thread blocks and a plurality of particle stacks, each thread block comprises N threads, and the N threads are used for processing N particles in parallel; the plurality of particle stacks comprise a first type of particle stacks and a second type of particle stacks; and the dose processing unit is used for collecting dose deposition information of the target particles according to the conveying behavior of the target particles in the medium, and updating the compression matrix according to the collected dose deposition information. The technical problems that in the prior art, when a Monte Carlo method is used for proton dose calculation, massive particles need to be simulated to obtain accurate dose distribution, so that the calculation time is too long, and the calculation efficiency is low are solved.

The invention discloses an accurate X-ray radiation dose measurement system based on artificial intelligence, which comprises the following steps: acquiring CT image data of a patient and pulse irradiation parameters of radiotherapy equipment through terminal equipment, and calculating a patient specific anatomical structure dynamic influence factor set, a pulse waveform time domain characteristic factor and a tissue interface scattering correction factor; all the parameters are substituted into a dose measurement formula to obtain an accurate X-ray radiation dose value; through a deep fusion image recognition technology (such as a high-resolution anatomical structure, tissue density gradient and heterogeneous region distribution provided by CT / MRI), a secondary particle scattering effect of a junction region of a tumor and a normal tissue can be accurately represented; and dynamic anatomical information (such as respiratory movement and organ displacement) in the image is combined to correct the time characteristic (such as dynamic change under an instantaneous high dose rate) of the pulse radiation field in real time, so that the dose calculation accuracy of a fast algorithm in a complex scene is remarkably improved.

The invention provides a proton dose distribution determination method and device based on a graphics processor, which can be applied to the technical field of medical radiation dose calculation. The method comprises the following steps: calculating pencil beam tracks of a plurality of pencil beams; obtaining respective dose nuclear parameters of the pencil beam at a plurality of intersection points; according to the radiation field dose truncation radius, voxels of interest are determined from tissue voxels in the tissue voxel grid, and the radiation field dose truncation radius represents the upper limit value of the acting distance of all pencil beams in one radiation field to generate remarkable contribution to dose distribution in the transverse direction; calling a plurality of threads to execute dose calculation tasks of the plurality of voxels of interest in parallel based on the respective dose kernel parameters of the plurality of intersection points to obtain voxel deposition doses of the voxels of interest; and determining a dose distribution result related to the specified tissue according to the voxel deposition doses of the plurality of voxels of interest.

The invention relates to the technical field of tumor radiotherapy, and discloses a radiotherapy parameter intelligent recommendation method based on disease species, target area volume and dose characteristics, and the method comprises the steps: firstly obtaining historical helical tomography radiotherapy data containing different disease species and dose schemes, and carrying out the standardization; then, non-iterative forward dose calculation based on full-factor experimental design is executed, and treatment simulation plans are generated in batches; then, dosimetry and efficiency indexes are extracted, and an optimization rule base containing a response surface model and a Pareto optimal solution set is constructed; and finally, processing new case features by using a decision tree model, and outputting a recommended collimator mode, a screw pitch, a modulation factor value and an expected index range. According to the method, data, a model and a decision closed loop are constructed, so that the defects that the traditional plan design depends on artificial experience, the trial and error cost is high and multiple targets are difficult to balance are overcome, and the efficiency and the quality consistency of the radiotherapy plan design are remarkably improved.

The invention discloses a radiation dose detection method and system for an irradiation cross-linked area, and belongs to the technical field of radiation dose detection.The method specifically comprises the steps that coordinates of a to-be-detected core point and coordinates of related points around the to-be-detected core point are input, and transient fluorescence spectrums, thermoluminescence signals and conductivity change data of all the points in an irradiation window are synchronously collected; constructing a physical configuration association model based on association point distribution, and forming a scattered field association data network; when the residual error between the actually measured data of the core point and the model predicted value exceeds a dynamic threshold value, activating the reverse solving process of the scattered field, reversely reconstructing a theoretical data sequence of the core point by using associated node data, and replacing interfered original data; and finally, inputting the reconstructed sequence into a dose calculation model, and outputting a corrected radiation dose value. According to the invention, measurement errors caused by local material non-uniformity and instantaneous interference can be effectively reduced, and the reliability of dose detection is improved.

The invention discloses an OpenMC-based BNCT dose full-process automatic calculation output method, and particularly relates to the technical field of boron neutron capture therapy dose calculation, and the method comprises the steps: reading a DICOM-CT image, automatically completing HU value segmentation, material assignment and voxel grid modeling, and generating an OpenMC geometry and material input card; setting a neutron / photon source, an operation mode and a counting grid, and executing Monte Carlo transport calculation; an ICRP flux-dose conversion coefficient library is built in, and dose calculation is automatically completed; the dose field is written into an Rt dose file, and the Rt dose file can be directly imported into mature medical image processing software for visual evaluation and plan optimization. According to the method, end-to-end automation from the CT image to the clinical available dose file is achieved, manual intervention is not needed, the BNCT dose calculation efficiency, precision and standardization level are remarkably improved, and a reliable tool is provided for BNCT dose simulation research.

The invention discloses an interactive lattice radiotherapy planning method and system based on a functional image, and relates to the technical field of radiotherapy, and the method comprises the steps: obtaining a radiotherapy positioning CT image of a patient and a functional metabolism image after the space registration with the radiotherapy positioning CT image; based on the radiotherapy positioning CT image and a preset safety boundary parameter, determining a candidate area of lattice layout in the tumor target area; for each candidate position in the candidate region, adaptively calculating lattice parameters for the position based on the corresponding SUV value of the position in the functional metabolism image; determining a final lattice center set from the candidate positions through an iterative screening algorithm on the basis of the calculated lattice parameters of the candidate positions and preset geometric constraints and biological constraints, and generating a lattice target region set on the basis of the final lattice centers and the lattice diameters corresponding to the final lattice centers; and outputting the lattice target region set for dose calculation of a radiotherapy planning system. Individualized dosage improvement really based on tumor internal heterogeneity is achieved.

The application relates to the technical field of medical data processing, and discloses a macroscopic cross-section database construction method, a dose determination method, a device and equipment, which comprises the following steps: setting multiple boron concentration values for the tissue types corresponding to a human body model; selecting corresponding neutron source parameters for the tissue types and the multiple boron concentration values, wherein the neutron source parameters comprise energy range values; dividing the energy range values into multiple discrete neutron energy groups; performing particle transport simulation based on the selected neutron source parameters, jumping between different neutron energy groups in the simulation process, and obtaining neutron reaction rates and neutron fluxes of the tissue types under the multiple boron concentration values and the multiple neutron energy groups; and obtaining neutron macroscopic cross-section values of the tissue types under the multiple boron concentration values and the multiple neutron energy groups based on the neutron reaction rates and the neutron fluxes, and constructing a multi-group macroscopic cross-section database. The application can improve the calculation efficiency of the radiation dose and improve the adaptability to individual metabolic differences during dose calculation.

A computer-implemented method for radiotherapy planning is disclosed, the method comprising: performing (202) a first dose calculation for one or more scenarios included in a first of a plurality of batches, where each of the plurality of batches comprises one or more scenarios associated with radiotherapy of a patient; initiating (204), in response to completion of the first dose calculation, an optimization process for one or more scenarios included in the first batch based on an output of the first dose calculation, where the optimization process seeks to optimize one or more first parameters of a treatment plan for radiotherapy of the patient; performing (206), in parallel with the optimization process, a further dose calculation for one or more scenarios included in a further batch of the plurality of batches; and in response to completion of the additional dose calculation, updating (208) the optimization process to include the one or more scenarios included in the additional batch such that the optimization process is further based on an output of the additional dose calculation.

A method for creating a media property map of a target region of an object, wherein the media property map provides multiple different media property values ​​in different segments of the target region, the media property values ​​depending on the medium in each of the segments, the method comprising: obtaining an image of the target region, wherein the target region includes a target treatment area and a surrounding area of ​​the target treatment area; processing the image to identify different components of the target region; segmenting the different components and classifying them into predetermined media categories; querying a media property value associated with each media category; and assigning the media property value to the respective corresponding component of the segmented target region.

The invention provides a flexible solar cell irradiation attenuation coefficient estimation method comprising the following steps: orbital parameters are combed, and spacecraft orbital parameters and space environment parameters are obtained; based on the orbit parameters and the space environment parameters, establishing an irradiation dose calculation model of the flexible solar cell; performing a ground equivalent test based on the irradiation dose calculated by the irradiation dose calculation model; and determining the irradiation attenuation coefficient of the solar cell in combination with test data and historical data. According to the method for estimating the irradiation attenuation coefficient of the flexible solar cell, the irradiation dose calculation model suitable for the flexible solar cell is constructed, the on-orbit performance attenuation coefficient of the solar cell array can be accurately obtained, and the accuracy of irradiation dose estimation is improved; scientific basis is provided for solar cell array design and on-orbit energy management, and reliability and design rationality of a spacecraft energy system are effectively improved.

The present application discloses a radiation dose rate assessment method, device, storage medium and equipment in three-dimensional space, which belongs to the field of radiation detection technology. The concentration data and physical parameter data of the radioactive nuclide at least one first position point in the three-dimensional space are obtained; the three-dimensional convolution of the photon flux rate of the second position point is determined, and its final kernel function is the kernel function composed of the interpolation basis functions of the first position point and the second position point obtained by approximating the original kernel function according to the FMM; the concentration data and the physical parameter data are convoluted using the three-dimensional convolution to obtain the target photon flux rate; the radiation dose rate in the three-dimensional space is assessed based on the physical parameter data and the target photon flux rate. The present application can quickly calculate the radiation dose rate of continuous and arbitrary discrete positions, reducing the computational complexity and computational cost; it can assess the radiation dose rate of complex building scenes based on the shielding matrix, and accelerate the dose calculation and improve the calculation accuracy through the nested grid FMM.

The invention discloses an insulin injection data management system, which relates to the technical field of medical health information and comprises a data acquisition module for acquiring injection operation data and blood sugar data from an insulin injection pen and lifestyle data input by a user; the intelligent analysis module is used for generating insulin dose recommendation information through a predefined dose calculation model on the basis of the injection operation data, the blood glucose data and the life style data, and generating injection site rotation recommendation information on the basis of injection site information in the injection operation data; the early warning prompt module is used for generating and outputting a dose early warning and a failure early warning based on dose information and temperature information in the injection operation data; and the medical care collaboration module is used for providing a data access interface for authorized medical care personnel and adjusting parameters of the dose calculation model based on remote instructions of the medical care personnel. And accurate and dynamic recommendation of dosage, scientific alternating guidance of injection parts and active early warning of dosage and failure are realized.

The invention discloses a heterogeneity correction model applied to radiation dose calculation, and relates to the technical field of radiotherapy. According to the content, the model comprises an input layer, a block embedding layer, an encoder, a bottleneck layer, a decoder and an output head. The bottleneck layer comprises two feature modeling modules. The input layer is used for receiving four-dimensional tensor data. And the block embedding layer is used for performing division processing on the four-dimensional tensor data through the three-dimensional convolution layer to determine a plurality of small blocks to be processed. The encoder comprises a sampling module used for sampling a plurality of small blocks to be processed and determining high-level features. The feature modeling module comprises a continuous window multi-head attention sub-block and a shift window multi-head attention sub-block, and is used for extracting local and global features and determining high-quality features based on input features. The output head is used for determining a heterogeneity correction coefficient based on the target features. Therefore, heterogeneity correction is carried out through the heterogeneity correction model, the calculation accuracy is improved, and the radiation dose calculation precision is improved.

The invention provides a rapid Monte Carlo dose calculation method based on statistical uncertainty perception noise reduction and application, and the method comprises the steps: carrying out the Monte Carlo dose simulation of a low particle number, and obtaining the middle rough dose distribution containing random noise and a corresponding voxel-level statistical uncertainty distribution diagram; acquiring an anatomical structure image of a patient, performing normalization processing and registration processing on the anatomical structure image, the middle rough dose distribution and the corresponding voxel-level statistical uncertainty distribution diagram, and constructing three-channel input data; the three-channel input data is input into a pre-constructed and trained statistical uncertainty perception denoising network model, the network model adopts a dual-path cavity convolution fusion architecture, and local features and global context features are extracted and fused; and the network model outputs denoised high-precision dose distribution as a final Monte Carlo dose calculation result. According to the method, the efficiency and the accuracy of radiotherapy plan design are remarkably improved.

The invention discloses a forward LatticeRT dose distribution optimization method and device based on an orthogonal double-layer grating. The method comprises the following steps: setting a prescription dose, arranging a radiation field with an equal interval angle, setting a blade position of an upper-layer grating, and forming a vertical stripe-shaped irradiation area; dose calculation is carried out in the forward direction, and a prescription dose line is stored as an organ structure; setting an irradiation range, and adjusting an irradiation angle within the irradiation range; according to the position of the structure on the BEV, the blade position of the upper grating is adjusted, so that the irradiation range can cover the structure; setting the blade position of the lower grating to form a lattice radiotherapy dose mode; generating a lattice wave crest irradiation area and a wave trough irradiation area according to the dose distribution; setting a comprehensive objective function; and an iterative optimization algorithm is adopted to adjust the blade position and the radiation field weight, so that the dose distribution is gradually close to the target function. The unique space structure of the orthogonal double-layer grating is utilized, the wave crests and the wave troughs are rapidly formed, and the Lattice plan manufacturing process is simplified.

The control circuit accesses information about a given patient. The information may include segmentation information depicting at least one treatment volume and at least one organ at risk, for example. The control circuit then defines a plurality of dose calculation sectors for the given patient based at least in part on the information about the given patient. These dose calculation sectors are not considered to be uniform in size. These teachings may then be used to optimize a radiation treatment plan, such as a volume modulated arc therapy radiation treatment plan, based at least in part on a plurality of dose calculation sectors to provide an optimized radiation treatment plan.

Embodiments described herein provide for training an artificial intelligence model to boost dose depositions. The artificial intelligence model receives medical images and a dose deposition determined according to a first dose deposition model. The artificial intelligence model modifies the received dose deposition determined according to the first dose deposition model such that the dose deposition simulates a dose deposition determined by a second dose deposition model.

The invention discloses a TCP and multi-NTCP combination optimal dose calculation method and system based on deep learning, relates to the technical field of radiotherapy, and aims to solve the problems of insufficient multi-source data integration, unbalanced multi-organ protection and low individualized precision in traditional dose optimization. The method comprises the following steps: acquiring a CT image of a target patient, a tumor and normal tissue dose-volume histogram (DVH), baseline clinical data and follow-up data after radiotherapy of a patient group; constructing a multi-modal feature data set and an annotation data set through spatial alignment and normalization processing, training a deep learning joint prediction model, synchronously outputting TCP values corresponding to candidate doses and NTCP values of at least three organs at risk, and constructing a fitting curve; and through a single-organ net income formula, a multi-organ comprehensive net income formula and an optimal dose screening formula, quantifying income-risk balance and screening an optimal dose for maximizing the comprehensive net income. According to the invention, through cooperation of deep learning and an exclusive formula system, dynamic quantitative balance of multi-organ unbiased protection and tumor control is realized, individualized precision and clinical landing of radiotherapy dose planning are improved, and the method is suitable for precise radiotherapy scenes of various solid tumors.

The invention provides a medical linear accelerator machine room radiation dose evaluation method and system. The method comprises the following steps: acquiring a radiotherapy plan through a DICOM-RT protocol, constructing a model based on computer room CAD parameters, converting structures such as a primary / secondary shielding body, a rosemary channel and the like into an ROI region containing material density, and fusing the ROI region with a patient CT image to form three-dimensional density distribution. After a dose calculation grid is generated, a radiotherapy plan dose algorithm is used to accumulatively calculate dose distribution after execution of all treatment plans, a dose value of a key shielding point POI and a dose volume histogram of an ROI area are mainly analyzed, and finally radiation protection efficiency is evaluated through a dose threshold value. The system comprises four modules: a receiving module for acquiring treatment data, a sketching module for establishing a machine room model, a calculation module for completing dose distribution superposition, and an evaluation module for judging a shielding effect. According to the method, a radiotherapy plan dose algorithm is innovatively applied to large-scale protection evaluation of the machine room, and quantitative analysis of radiation safety of the machine room is realized.

A boron neutron capture therapy system and a treatment planning generation method thereof, the boron neutron capture therapy system comprising a neutron beam irradiation device, a treatment planning module and a control module. The neutron beam irradiation device is used to generate a therapeutic neutron beam and irradiate to a boron-containing drug-incorporated irradiated body to form an irradiated site during irradiation therapy. 10 B). The treatment planning module performs dose simulation calculation according to medical image data of the irradiated site and parameters of the therapeutic neutron beam generated by the neutron beam irradiation device, and generates a treatment plan, wherein the medical image data of the irradiated site comprises tissue-related information and boron 10 B) concentration-related information. The control module calls the treatment plan corresponding to the irradiated body from the treatment planning module, and controls the neutron beam irradiation device to perform irradiation therapy on the irradiated body according to the treatment plan. The boron neutron capture therapy system and the treatment planning generation method thereof can improve the accuracy of model establishment and dose calculation.

The invention belongs to the technical field of data processing, and particularly relates to an electric energy meter production environment comprehensive quality evaluation method and system, and the method comprises the steps: collecting the real-time environment data in an electric energy meter aging room and the operation load data of an electric energy meter; according to the real-time environment data, the instantaneous comprehensive stress intensity applied to the electric energy meter by the environment at the current moment is determined in combination with the temperature data at the previous moment; performing time dimension accumulation calculation on the instantaneous comprehensive stress intensity in combination with operation load data to obtain an accumulated aging effective dose of the current batch of electric energy meters; and determining a production consistency evaluation index according to the ratio of the cumulative aging effective dose to a preset target dose and the stress fluctuation degree in the aging process, and judging whether the aging quality of the electric energy meter is qualified or not based on the cumulative aging effective dose and the production consistency evaluation index. The method can achieve the dynamic evaluation of the aging quality of the electric energy meter based on the effective aging dose calculation.

An accumulated dose distribution is generated using a mass-weighted dose summation and / or four-dimensional dose calculation. Medical image data are accessed with a computer system, where the medical image data contain at least a reference image and a daily image acquired from a patient. A deformation map is generated from the medical image data using a deformable image registration between the reference image and the daily image. Transferred dose data are generated by mapping dose data from the daily image to the reference image using the deformation map or recalculated using mapped energy and mass data. The accumulated dose distribution is generated using a mass-weighted summation of the transferred dose data, in which the transferred dose for a fraction is weighted by a mass weighting value corresponding to a ratio of a transferred mass density image for that fraction and an average over of transferred mass density images over all fractions.

According to the intelligent deodorization device and method, the problem of dosage deviation possibly caused by calculation only according to concentration and volume in the prior art is solved, and calculation of basic neutralization dosage is more suitable for an actual scene; meanwhile, in combination with adaptive adjustment of an environment correction coefficient on temperature and humidity, the accuracy of dose calculation is improved, not only is incomplete deodorization caused by insufficient dose avoided, but also neutralizer waste and possible secondary pollution caused by excessive dose are prevented, and finally efficient utilization of the neutralizer and thorough elimination of odor of a target space are achieved; the practicability and the reliability of the intelligent deodorization method are improved.