334 results about "Dose distribution" patented technology

The invention belongs to but is not limited to the technical field of three-dimensional space dose visualization, and discloses a three-dimensional nuclear emergency radiation field calculation and visualization method and system, based on a point nuclear method, a cumulative factor, mass attenuation factor and flux rate-dose rate conversion factor database is established, a mean free path solving algorithm is optimized, and a three-dimensional nuclear emergency radiation field is obtained. The geometric types of radioactive sources are expanded, and the dose calculation efficiency is improved through parallel calculation; plane dose rate drawing at a certain height is realized based on a two-dimensional texture mapping method; three-dimensional space dose rate contour surface drawing is realized based on a moving cube algorithm; and three-dimensional space dose rate volume rendering is realized based on a three-dimensional texture volume rendering technology. Radiation field dose calculation, three-dimensional radiation field dose visualization and GIS are integrated, and the system is used as a subsystem of a nuclear emergency aid decision simulation platform. The dose distribution diagram in the area can be judged more visually, and the method has a good help effect on nuclear emergency command.

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 belongs to the technical field of medical treatment, and discloses a radiotherapy protection system for reducing normal tissue damage, and the system comprises a real-time imaging and monitoring module which employs high-speed CT or MRI equipment to obtain 4D images of a target region and surrounding tissues of a patient in real time in a treatment process; the dynamic protection dose distribution module is used for dynamically calculating dose distribution of each radiation according to the real-time imaging data, optimizing an irradiation path and reducing the stress of normal tissues; the intelligent feedback control module is used for detecting the accumulated dose of a target region and normal tissues in real time and dynamically adjusting an irradiation strategy; inputting the real-time image and the dose monitoring data into a treatment planning system, and updating an irradiation plan; the user interaction module provides a radiotherapy real-time display interface; patient physiological data is monitored in real time. According to the invention, through dynamic real-time monitoring, dose distribution optimization and intelligent feedback control, the limitation of the traditional radiotherapy technology on real-time performance and protection effect is broken through. The system significantly reduces damage to normal tissues, improves treatment precision and patient experience, and has wide clinical application value.

The invention provides a non-equidistant lattice distribution optimization method based on local dose constraint. The method comprises the following steps: generating an initial lattice based on a patient image and a delineated target region; calculating and storing a dose kernel in advance based on a Monte Carlo algorithm; calling a dose core to carry out rapid dose optimization and calculation; establishing an independent peripheral subspace dose evaluation region and a local dose constraint condition for each lattice target region; establishing a multi-objective function for lattice target region position optimization; dynamically adjusting lattice positions and intervals by using a rapid simulated annealing method or a gradient descent method until target region position distribution and dose distribution meeting a dose multi-objective function and constraint conditions are generated; according to the invention, through dynamic adjustment of the lattice spacing and position and combination of the patient specific anatomical structure, accurate control of the valley dose around each lattice is realized, so that the problems of non-uniform target dose distribution and insufficient valley dose control in traditional equal spacing lattice radiotherapy are solved.

The present disclosure provides systems and methods for automated scan preparation and real-time monitoring / adjustment in medical imaging. The automated scan preparation may include positioning a target subject to be scanned by a medical imaging device, determining a rotation scheme of the medical imaging device, targeting a scan region of the target subject with an imaging isocenter of the medical imaging device, determining target position(s) of component(s) of the medical imaging device, performing a virtual scan, generating a reference subject model representing an internal structure of the target subject, or the like. The real-time monitoring / adjustment operations may include achieving automatic brightness stabilization, monitoring a posture of the target subject, adjusting the position of component(s) of the medical imaging device, estimating a dose distribution, monitoring a treatment of the target subject, performing a motion correction, or the like.

The invention discloses a gravitational field model-based lattice space segmentation radiotherapy lattice point optimization method, and relates to the technical field of radiotherapy. According to the method, by combining a PET-CT functional image, a key region, especially a hypoxic region (functional target region), of a tumor is recognized more accurately, and the positions and the distances of lattice points are dynamically adjusted according to biological characteristics of the tumor; arrangement of lattice points is dynamically adjusted through a gravitational field model, it can be guaranteed that a high-dose area accurately covers a key area of a tumor, unnecessary side effects can be reduced to the maximum extent, the risk of tumor recurrence is reduced, the method can better adapt to functional heterogeneity of the tumor, personalized treatment is achieved, and the method has good application prospects. And the influence on normal tissues is reduced while the treatment accuracy is improved, a more reliable treatment scheme is provided for treatment of complex tumors, and accurate dose distribution aiming at different tumor biological characteristics is realized.

The invention discloses an ultra-high dose rate radiotherapy plan optimization system based on compensator modulation, and relates to the technical field of radiotherapy. A data acquisition module is used for acquiring medical image data of a patient and receiving a clinical target; the clinical target comprises a target region prescription dose, an organ-endangering limit and a minimum dose rate threshold value required for triggering and maintaining a FLASH effect; and the FLASH biological effect evaluation module is used for calculating FLASH biological effective dose distribution corresponding to the physical dose distribution through an embedded biological effect model based on the input physical dose distribution and dose rate distribution. According to the method, the physical dose is converted into the accurate FLASH biological effective dose through the improved linear quadratic model embedded with the FLASH correction factor, the target tumor killing effect is guaranteed, normal tissue protection is enhanced with the help of the tissue differentiation correction factor, the industrial pain point that the physical dose reaches the standard but the biological effect does not reach the expectation is effectively solved, and the application prospect is wide. And the treatment plan better meets the clinical curative effect and safety core requirements.

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 present application provides a plan adjustment method for radiotherapy, a radiotherapy system, and a related apparatus. The method comprises the following steps: S1, acquiring simulated CT information and treatment plan information of a patient, the simulated CT information comprising a simulated CT image and region division information corresponding thereto; S2, measuring, in the current session of radiotherapy corresponding to the treatment plan information, Cerenkov radiation emitted by the patient due to particle radiation exposure; S3, acquiring irradiation exposure dose information of an irradiation target region and an organ at risk in the treated region; S4, determining, according to the dose information of the target region and the organ at risk and the treatment plan, whether the treatment plan for subsequent irradiation fractions needs adjustment; and S5, if so, adjusting the treatment plan for subsequent fractions according to dose distribution of an irradiation exposure region and a therapeutic prescription corresponding to the patient. In the present application, the Cerenkov radiation emitted by the patient is detected to judge the quality of the treatment plan, which improves the accuracy of plan adjustments in radiotherapy and the safety of radiotherapy.

The invention relates to the technical field of computers, and discloses an automatic segmentation and intelligent plan generation method and device suitable for self-adaptive radiotherapy of prostate cancer. Comprising the following steps: acquiring medical image data of a treated object, clinical dose data of a target area and an organ at risk in a focus area of the treated object, and clinical treatment data of a preset priority level; performing automatic segmentation based on the medical image data to obtain target segmentation data; performing dose distribution prediction according to the target segmentation data to obtain initial dose distribution data, and performing iterative optimization on the initial dose distribution data by using clinical treatment data to obtain target dose distribution data of the treated object; and performing iterative optimization of a radiotherapy plan based on the target dose distribution data, and generating a target radiotherapy plan of the treated object. Therefore, on the basis of realizing accurate, efficient and automatic segmentation of the prostate cancer target region and the endangered organ, multi-round iterative optimization of dose distribution and the radiotherapy plan is carried out, and finally a high-quality target radiotherapy plan is obtained.

The invention provides a composite collimator and a control method thereof, a radiotherapy system and a dose delivery method thereof, and relates to the technical field of radiotherapy, and the composite collimator comprises a grating and a diaphragm which are sequentially arranged in the direction of a beam center axis, the plurality of blades move to form a grating channel through which a radiation beam can pass; the diaphragm is provided with a collimation channel, and the diaphragm can move relative to a beam center axis; when the diaphragm moves to enable the collimation channel to be located at the central axis of the beam, the radiation beam forms a focusing radiation field in a target area through the grating channel and the collimation channel; and when the diaphragm moves to enable the collimation channel to deviate from the beam center axis, the radiation beam forms a conformal radiation field in the target area through the grating channel. Through switching between the conformal radiation field and the focusing radiation field, a flexible irradiation scheme is provided, so that the dose distribution effect can be improved, and the radiotherapy effect is improved.

The invention discloses a deep learning model for radiotherapy dose distribution prediction and a radiotherapy plan generation method, and the deep learning model is constructed based on a UNet model, is obtained by inputting a training data set into the UNet model for training, and comprises a coding part which is composed of a mixing module and a down-sampling layer and is used for extracting data features, and the down-sampling layer uses maxpoo; the decoding part is composed of a decoding layer mixing module and an up-sampling layer and is used for gradually recovering the size of the original resolution, and the up-sampling layer adopts transposition convolution; the jump connection part is used for connecting the encoding part and the decoding part, and extracting features which are beneficial for the decoding part to recover to the original resolution from the encoding part; wherein the mixing module is composed of a plurality of branch paths, and outputs of the plurality of branch paths are added to serve as final output. The deep learning model is constructed by using a multi-branch path combination strategy, three-dimensional dose distribution can be quickly and accurately predicted, and plan generation in radiotherapy can be quickly completed.

The present disclosure provides systems and methods for automated scan preparation and real-time monitoring / adjustment in medical imaging. The automated scan preparation may include positioning a target subject to be scanned by a medical imaging device, determining a rotation scheme of the medical imaging device, targeting a scan region of the target subject with an imaging isocenter of the medical imaging device, determining target position(s) of component(s) of the medical imaging device, performing a virtual scan, generating a reference subject model representing an internal structure of the target subject, or the like. The real-time monitoring / adjustment operations may include achieving automatic brightness stabilization, monitoring a posture of the target subject, adjusting the position of component(s) of the medical imaging device, estimating a dose distribution, monitoring a treatment of the target subject, performing a motion correction, or the like.

The invention relates to a self-adaptive radiotherapy plan determination method, a self-adaptive radiotherapy system and a storage medium. The method comprises the following steps: acquiring a current region-of-interest segmentation result and current image features corresponding to a current image of an object; according to the segmentation result of the current region of interest and the current image features, candidate radiotherapy plans are selected from a plan library of the object, and the plan library comprises historical images of the object and corresponding historical radiotherapy plans; calculating a calculated dose distribution corresponding to the current image based on parameters in the candidate radiotherapy plan; determining the applicability of the candidate radiotherapy plan for the current image according to the calculated dose distribution, the segmentation result of the current region of interest and the features of the current image; and the target radiotherapy plan for the current image is determined based on the applicability, so that the generation efficiency and effectiveness of the adaptive radiotherapy plan are improved.

The invention provides a particle dose determination method and device, electronic equipment and a storage medium, and relates to the field of physics and computers, in particular to application of physics and computer technologies in the field of radiation medical treatment. The particle dose determination method comprises the following steps: respectively guiding a particle beam to move through M groups of scanning parameters to obtain a plurality of transverse radiation field dose distribution data; wherein each group of scanning parameters corresponds to a plurality of transverse radiation field dose distribution data, and M is a positive integer; according to the plurality of transverse radiation field dose distribution data, calculating to obtain a plurality of first radiation field dose distribution data corresponding to each group of scanning parameters; wherein the dimension of the first radiation field dose distribution data is higher than that of the transverse radiation field dose distribution data; based on scanning parameters and the first radiation field dose distribution data, obtaining a target model used for determining radiation field center dose distribution; and inputting the target scanning parameter into the target model, and determining the delivery dose according to the target radiation field center dose distribution output by the target model.

Systems and methods for evaluating and presenting robustness of a radiotherapy treatment plan for use in radiotherapy are discussed. An exemplary system includes a processor to generate, in a radiation simulation in accordance with the treatment plan under evaluation, dose distributions at an anatomical structure under a nominal condition and one or more artificially imposed uncertainty conditions, determine a dose distribution characteristic for the anatomical structure using the received dose distributions, and generate a robustness indicator of the treatment plan. The dose distributions may be determined at a target structure and one or more structures at risk, and presented graphically in a three-dimensional dose-volume-structure space. An output circuit can output the dose distribution characteristic or the robustness indicator to a user or a treatment planning system.

The invention relates to the technical field of intelligent disinfection, and discloses an intelligent ultraviolet disinfection control system and method based on environmental perception, and the system comprises an information extraction module, a radiation model construction module, a dose distribution module, a disinfection module, a data feedback module and a disinfection termination module. Wherein an initial model is constructed based on three-dimensional point cloud data and reflectivity characteristics, reflectivity compensation is performed on the initial model, and an ultraviolet radiation field attenuation model is obtained; coupling the ultraviolet radiation field attenuation model with an ultraviolet sterilization threshold database to obtain an ultraviolet dose spatial distribution map; the to-be-disinfected object is disinfected according to the ultraviolet dose space distribution diagram; dynamically correcting the ultraviolet radiation field attenuation model based on irradiance feedback data of the to-be-disinfected object during disinfection to obtain an ultraviolet dose regulation and control instruction of the to-be-disinfected object; when the ultraviolet dose regulation and control instruction reaches a biosafety threshold value, the disinfection process is terminated; the intelligent disinfection efficiency can be improved.

The invention relates to the technical field of clinical medicine, and discloses an AI prediction system for relapse after radiotherapy of local advanced rectal cancer, and the system comprises a multi-modal biological image database building module which is used for collecting clinical data, image data, radiotherapy target region and dose distribution data, radiobiological data and genomics information of a patient, integrating the data to establish a database; a feature extraction and screening module; a prediction model construction module; a model verification and optimization module; and a clinical application evaluation module. According to the invention, information of patients in multiple aspects such as clinic, image, radiotherapy target area and dose distribution, radiobiology and genomics is widely collected, and the multi-modal biological image database is integrated and established, so that various factors influencing rectum cancer relapse after radiotherapy can be comprehensively covered; a rich, accurate and comprehensive data basis is provided for subsequent accurate analysis and prediction, and the accuracy and reliability of prediction of relapse conditions after radiotherapy are improved.

The invention relates to the technical field of beam measurement, and provides a beam integration device, which comprises a logic control module and a plurality of integration modules, each integration module is used for being correspondingly connected with one output channel of a dose distribution detector, and each integration module comprises a current gear selection circuit, an integration circuit and a polarity discrimination circuit, the current gear selection circuit comprises a plurality of current gear channels; the current gear selection circuit is used for selecting a target current gear channel to be connected with an output channel corresponding to the dose distribution detector under the control of the logic control module, and converting a current pulse signal output by the output channel corresponding to the dose distribution detector into a voltage signal; the polarity discrimination circuit discriminates the polarity of the voltage signal and converts the voltage signal into the polarity required by the integrating circuit. According to the beam current integration device, simultaneous integration of multi-channel bipolar current pulse signals is realized, and the integration range is automatically switched according to the change of the current pulse signals.

Disclosed herein are systems and methods for adapting and / or updating radiotherapy treatment plans based on biological and / or physiological data and / or anatomical data extracted or calculated from imaging data acquired in real-time (e.g., during a treatment session). Functional imaging data acquired at the time of radiation treatment is used to modify a treatment plan and / or dose delivery instructions to provide a prescribed dose distribution to patient target regions. Also disclosed herein are methods for evaluating treatment plans based on imaging data acquired in real-time.

The invention relates to the technical field of dosimetry, in particular to a rapid dose evaluation method and device for individualized targeted radionuclide treatment.The method comprises the steps that labeled nuclides, drug ligands and image data of a patient are obtained, and corresponding standard S values are selected according to the labeled nuclides and the drug ligands; the method comprises the following steps: segmenting first-time-phase CT image data to obtain a segmentation mask of a target organ, calculating an individualized S value based on the segmentation mask, generating an individualized voxel model, registering the SPECT image data and the CT image data to obtain organ-level source item parameters and voxel-level source item parameters, and calculating an individualized S value based on the individualized voxel model to obtain an organ-level source item parameter and a voxel-level source item parameter; and according to the organ-level source item parameter and the voxel-level source item parameter, respectively obtaining an organ-level dose evaluation result and a voxel-level dose evaluation result, and comprehensively evaluating source target organ dose distribution. Therefore, the problems that the dose conversion coefficient lacks calibration, the voxel model is difficult to balance the calculation speed and precision and the like are solved, errors caused by individualized differences are reduced, and the calculation accuracy and speed are guaranteed.

The invention relates to a self-adaptive radiotherapy dose optimization method and device and a storage medium, which are used for optimizing dose distribution in radiotherapy. Through combination of deep reinforcement learning (DRL) and a heuristic algorithm (a particle swarm optimization algorithm), the method maximizes the dose of a tumor area, and protects surrounding normal tissues at the same time. Firstly, an anatomical structure and a tumor area of a patient are extracted through medical image data, and initial dose distribution is generated; then, the deep reinforcement learning agent adjusts dose distribution according to the dynamic anatomical change of the patient, a heuristic algorithm is further optimized, and a local optimal solution is avoided; real-time feedback in the treatment process is used for adjusting dose distribution, and accuracy and timeliness of a treatment scheme are ensured. Finally, the generated optimal dose distribution scheme is provided for a clinician to refer, dose maximization of the tumor area is ensured, and normal tissue is protected. According to the method, the precision and effect of radiotherapy are improved, and a personalized treatment scheme is provided.

The invention relates to the technical field of radiation dose calculation, in particular to a radiation dose calculation method and device based on a V-Net network. The method comprises the following steps: acquiring a CT image and light beam flux information for a focus area of a patient to be treated, wherein the light beam flux information represents parameter information of a light beam for performing radiotherapy on the patient to be treated; and on the basis of the CT image and the beam flux information, through a pre-trained V-Net network, performing radiotherapy dose calculation for a focus area of a patient to be treated, and generating a dose distribution diagram. According to the method, the dose distribution diagram can be automatically generated, human intervention is reduced, and the clinical working efficiency and the adaptability of a treatment plan are improved. Moreover, the pre-trained V-Net network can effectively capture features in the CT image, the calculation speed is greatly improved, the precision of the generated dose distribution diagram is equivalent to the calculation precision of the Monte Carlo method, and both the speed and the precision are taken into account.

The invention discloses a U-shaped groove grating ion beam etching method based on a mask shadow effect, and relates to the technical field of U-shaped groove etching, and the method comprises the steps: placing a substrate with a photoresist grating mask in an inclined manner, and enabling an ion beam to bombard the photoresist grating mask in an inclined incidence manner; through a shadow effect generated by a photoresist grating mask on an ion beam, the etching dose distribution of different areas on the surface of a substrate is regulated and controlled, so that the etching dose of the central area of the groove bottom is greater than that of the areas on the two sides, and the U-shaped groove with a smooth and gradually-changed bottom contour is directly etched and formed. By constructing the smooth transition U-shaped groove bottom structure, sharp edges and corners are thoroughly eliminated, and the phenomenon of electric field concentration is remarkably relieved, so that the damage risk under high-power laser irradiation is effectively reduced, the stability of the grating in an extreme environment is improved, and the service life of the grating in the extreme environment is prolonged.

The invention relates to the technical field of radiotherapy dose analysis, in particular to a radioactive cardiotoxicity prediction system based on multi-modal dynamic fusion and a quantitative evaluation method. According to the system, medical images, radiotherapy plans and clinical parameters are acquired through the multi-modal data acquisition module; the image preprocessing and three-dimensional reconstruction module processes the image data and reconstructs a heart model containing a substructure; the dynamic dose module is combined with the four-dimensional respiratory gating image and the dose matrix to generate time sequence dose distribution; the feature fusion and prediction module extracts multi-modal features, performs calculation by using a graph convolutional network, a long-short term memory network and an attention mechanism, and outputs a cardiotoxicity risk quantitative index; and finally generating a heart substructure level risk thermodynamic diagram and a structured report. According to the method, dynamic dose modeling, heart substructure level refined analysis, multi-source information fusion and individualized prediction are realized, and the accuracy, interpretability and clinical auxiliary decision-making value of cardiac toxicity risk assessment are remarkably improved.

The invention relates to the technical field of medical treatment, in particular to a deformation registration method and system, a self-adaptive treatment planning method and a treatment planning system which are used for improving the accuracy of image deformation registration, and the method comprises the steps: obtaining a plan image, a fractional image and dose distribution data corresponding to an initial treatment plan of a patient; inputting the plan image, the graded image and the dose distribution data corresponding to the initial treatment plan of the patient into a trained deformation registration model, performing deformation registration on the graded image and the plan image, and outputting a deformation field; wherein the trained deformation registration model is obtained based on dose distribution consistency loss training between dose distribution data corresponding to the initial treatment plan and deformation dose distribution data corresponding to the deformation field.

The invention relates to the technical field of radiotherapy, and discloses a method for generating a boron neutron capture therapy plan, computer equipment and a storage medium. Comprising the following steps: based on current state data of neutrons, determining first section data, second section data and a current transport distance of the neutrons at a current position, and judging whether the neutrons collide or not; wherein the first cross section data is used for describing the macroscopic cross section of nuclides except boron, and the second cross section data is used for describing macroscopic cross section neutrons obtained through calculation according to the boron concentration of the current grid and the microcosmic cross section of the nuclide boron; and under the condition that neutrons do not collide and the neutrons are transmitted from the current grid to the next grid through the surface, if the two grids are made of the same material, updating the second cross section data based on the boron concentration of the next grid to calculate the dose, and finally generating a boron neutron capture therapy plan by using a dose distribution calculation result. Therefore, only the cross section data related to the boron concentration is updated in the penetrating surface, and the calculation efficiency is optimized.

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 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.