1309 results about "Normal tissue" patented technology

The invention relates to the technical field of image annotation, in particular to a medical image auxiliary annotation method and system based on image processing, and the method comprises the following steps: obtaining medical image data, and carrying out the edge enhancement processing of the image data; performing preliminary labeling on the central necrosis layer, the edge active layer and the peripheral normal tissue layer to generate preliminary labeling areas of different focus levels; extracting textural features, morphological features and density features of each level, and converting the textural features, morphological features and density features into feature vectors for storage; forming a multi-level lesion association model; adjusting the boundary positions of the layers, and ensuring that the relative position relation between the layers is reasonable; dynamically updating the level annotation according to the change characteristics; and outputting a labeling layer containing the multi-level focus characteristics of the central necrosis area and the edge active area. Compared with an existing single-level or coarse-grained marking method, the method has the advantages that the hierarchical expression effect of the focus area is improved, and the detail level of the focus in the complex form is clearly presented.

The invention relates to the technical field of medical image processing and tumor treatment, and provides a tumor image boundary identification method and system fused with a fluorescence boundary, and the method comprises the steps: collecting a tumor dynamic fluorescence image sequence and breathing waveform data through a fluorescence imaging device; performing multi-scale noise suppression processing on the image sequence to generate a preprocessed image without artifacts; extracting fluorescence intensity distribution characteristics through a multi-layer characteristic weighted fusion network and generating an intensity distribution matrix; constructing a motion compensation model according to the breathing waveform data, and correcting the boundary displacement of the intensity distribution matrix; fusing the corrected fluorescence features and the tumor tissue texture features to generate an initial tumor boundary contour; iterative topological optimization is carried out on the initial boundary, and boundary discontinuity is eliminated; and mapping the optimized boundary to a space coordinate system of the laser treatment equipment, generating a boundary mapping model and updating the boundary mapping model in real time. The precision and safety of laser treatment can be improved, and damage to normal tissue is reduced.

The invention discloses a tumor radiotherapy dose calibration method, and relates to the technical field of tumor radiotherapy, and the method comprises the steps: collecting multi-modal data in real time through 4D-CT, MRI and the like, extracting dynamic features through space-time registration, calculating a risk organ dose ratio and a tumor target dose deviation rate, and constructing a comprehensive evaluation function. The method has the advantages that the multi-modal dynamic data of the tumor target area are synchronously collected in real time, the space-time joint registration algorithm and the time sequence weight factor are combined, the limitation that existing static calibration depends on fixed parameters is broken through, and the method is suitable for the multi-modal dynamic data of the tumor target area. According to the method, 95% dose coverage of a tumor target region is guaranteed, and meanwhile, organ-endangering peak value receiving amount is controlled within a certain range of a clinical tolerance threshold value, so that the risk of excessive irradiation of normal tissues is reduced, and the radiotherapy dose calibration precision is prompted based on the deviation rate of a traditional method.

The invention discloses an auxiliary film reading method and system based on artificial intelligence, and the method comprises the steps: 1, collecting a pathological WSI, an electronic medical record, detection data and equipment parameters, correcting the equipment difference through adaptive dyeing normalization, and constructing a structured data package associated with an ID-timestamp of a patient; 2, developing a dynamic branch CNN, migrating teacher model knowledge through knowledge distillation, and introducing federated learning; step 3, the edge generates a thermodynamic diagram to mark a suspicious area, and the cloud outputs a structured report; step 4, constructing a normal tissue feature space by the variational auto-encoder, detecting abnormal slices and triggering expert re-checking; a reverse automatic encoder generates a pseudo-health image to compare and position a pathological area, and dynamic weight adjustment balances the federal learning convergence speed; 5, integrating the thermodynamic diagram, the gene data and the clinical indexes by a three-dimensional platform, and supporting multi-dimensional superposition display; webGL realizes browser end rendering, and NLP automatically generates a report abstract marked with a key evidence chain and is in butt joint with an international diagnosis and treatment guide.

A computer-based adaptive decision support system for radiotherapy, including: • a patient data acquisition module configured to acquire patient-specific clinical data, including an anatomical image, a physiological signal, and genomic data; • a preprocessing and feature extraction modality compatible with normalizing, preprocessing and extracting statistical features from the acquired data; • a status estimator used to provide a dynamic representation of the patient's treatment evolution status based on radiation, biological, dosimetric characteristics; • customized action rescaler to define a series of clinically meaningful treatment adjustments depending on the patient's current condition; • a reward function engine used to calculate therapeutic outcome scores based on the probability of tumor control, the probability of complications in normal tissue, and other predetermined factors; • a reinforcement learning agent that can learn and update treatment adaptation policies based on deep reinforcement learning techniques; • a clinical decision dashboard that provides recommended treatment adjustments and personalized interaction with the physician; and • a clinical integration interface adapted for exporting the customized treatment plan to an external treatment planning or delivery system.

The invention relates to a focus identification and segmentation method and system based on a lung CT image, and the method comprises the steps: obtaining three-dimensional lung CT image data of a patient, cutting the three-dimensional lung CT image data into a plurality of two-dimensional lung CT image pictures, and adding serial numbers; carrying out image preprocessing on the plurality of two-dimensional lung CT images, and carrying out image feature extraction on the preprocessed images by using a specified image feature extraction algorithm; further detecting the lesion edge of the lesion feature data of the extracted two-dimensional lung CT image; based on an edge detection result of the two-dimensional lung CT image picture, segmenting a lung focus and normal tissues to generate a plurality of two-dimensional lung focus pictures only having focus tissues; and carrying out image fusion on the two-dimensional lung focus image according to a specified interval based on the added serial number, and filling a focus area between the specified intervals to obtain a complete three-dimensional lung focus image. The focus in the medical image of the patient can be accurately and efficiently identified and segmented in the three-dimensional space.

The invention discloses a skin targeted therapy laser control method and system based on a dual-wavelength synergistic effect, and the method comprises the steps: collecting the real-time morphological characteristics and pigment distribution data of skin tissues through a multispectral imaging unit, and recognizing the optical characteristic parameters of a target treatment region; generating a dual-wavelength combination scheme through a dynamic wavelength selection algorithm based on the optical characteristic parameters and the tissue structure characteristics of the target treatment area; according to a dual-wavelength combination scheme, generating a synergistic laser sequence with a specific pulse interval and energy ratio; the synergistic laser sequence is converted into a driving signal, and a dual-wavelength laser is controlled to output composite laser; and laser output parameters are dynamically adjusted through real-time thermal diffusion monitoring and an optical feedback mechanism. By utilizing the embodiment of the invention, accurate and selective heat dissipation of skin target tissues can be realized, surrounding normal tissues are effectively protected, the treatment safety and effectiveness are improved, and side effects are reduced.

The invention relates to the field of medical equipment, and discloses an intracavity radiofrequency ablation system. The system includes a radio frequency generator, a catheter with a heating element, a pressure sensor, and a temperature sensor, a processor, and a display. By monitoring the temperature and the pressure in real time and dynamically adjusting the radio frequency energy output power, the safety and the accuracy of the treatment process are ensured. The system can automatically adjust treatment parameters according to the real-time contraction condition of the cavity tissue, prevent overheating, reduce damage to normal tissue, provide visual tissue contraction feedback and improve the treatment effect.

The utility model discloses a tumor electric field treatment device and a treatment system, the tumor electric field treatment device is provided with a frame body and a pole piece module, the frame body forms a skeleton structure of the treatment device, the pole piece module is attached to the frame body, the pole piece module is provided with a plurality of electrode contacts, and each electrode contact can form an active contact or a passive contact. The active contact and the radio frequency generation module can form a loop; after the treatment device is implanted into a tumor excision part, all the electrode contacts form active contacts, and all the electrode contacts and the radio frequency generation module form a loop to distinguish normal tissues from pathological tissues; after the normal tissue and the lesion tissue are distinguished, the electrode contacts in the normal tissue area form passive contacts, and the electrode contacts in the lesion tissue area form active contacts, so that targeted treatment of the lesion tissue is realized, and side effects generated by electric field treatment are reduced.

The invention relates to the technical field of biological information, in particular to an immunoreaction evaluation method based on tumor neoantigen activity sorting. The method comprises the following steps: obtaining genome data of tumor and normal tissues through whole exon sequencing, extracting multi-dimensional features of candidate somatic mutation, and screening by combining a Gaussian mixture model and a Transform model to obtain a high-confidence mutation genome set; predicting the HLA genotype of a patient based on sequencing data, translating and mutating into a peptide fragment, predicting the binding affinity of the peptide fragment and an MHC molecule by using an XGBoost model, and calculating a new antigen activity score sequence in combination with various parameters; and finally, synthesizing a new antigen peptide fragment according to a sorting result, carrying out in-vitro co-culture to detect an IFN-gamma secretion result, and dynamically optimizing a characteristic combination coefficient through a PPO algorithm to realize intelligent iterative updating, so that the accuracy of new antigen screening and the immunoreaction prediction capability are remarkably improved.

The invention discloses a self-adaptive aid decision-making method, system and device for patient radiotherapy, and a medium, and relates to the field of smart medical treatment. The method comprises the following steps: standardizing and preprocessing multi-source original data; performing automatic segmentation and change detection on tumor and normal tissues based on the processed data; delineating a tumor target region and a normal tissue in radiotherapy in a detection result; generating radiation therapy dose distribution according to the sketching result; evaluating the radiation treatment dose distribution by adopting an optimization evaluation method to generate a plurality of alternative treatment schemes; determining an optimal treatment regimen based on the plurality of alternative treatment regimens; and performing radiotherapy based on the optimal treatment scheme, monitoring anatomical changes of the patient in real time in the radiotherapy process, and dynamically adjusting the optimal treatment scheme. According to the invention, a plurality of operations of patient radiotherapy can be effectively integrated, and precision and individuation of patient radiotherapy can be realized, so that complex changes in the treatment process can be better coped with, and the overall treatment effect can be improved.

An objective of the present disclosure is to provide anti-CD137 antigen-binding molecules which have immunocyte-activating effect, cytotoxic activity, or anti-tumor activity, and meanwhile have reduced effect on non-tumor tissues such as normal tissues and produce less side effects, and methods of using the same.Anti-CD137 antigen-binding molecules which have immunocyte-activating effect, cytotoxic activity, or anti-tumor activity, and meanwhile have reduced effect on non-tumor tissues such as normal tissues and produce less side effects, are provided by discovering and producing CD137 antigen-binding molecules whose binding activity to CD137 depends on various substances (for example, small molecule compounds) in target tissues. Methods of using the same, pharmaceutical formulations, and such are also provided.The present disclosure also provides an antigen-binding molecule whose binding activity to an antigen varies depending on a small molecule compound, a preparation method thereof, and uses thereof.

The invention relates to the field of sound velocity, opto-acoustic and ultrasonic imaging, in particular to a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging method and a dynamic sound velocity self-adaptive ultrasonic opto-acoustic bimodal imaging system. The method comprises the following steps: acquiring an ultrasonic signal and a photoacoustic signal; reconstructing a sound velocity distribution diagram according to the ultrasonic signal; based on the sound velocity distribution diagram, reconstructing a related time delay diagram; and reconstructing an ultrasonic image and a photoacoustic image based on the related time delay graph. The problems that a traditional sound velocity correction method is limited in application range, inconvenient to operate, high in cost, low in resolution and the like are solved; the adopted sound velocity correction algorithm is high in resolution, is suitable for various transducers of linear arrays, convex arrays, ring arrays, spherical arrays and the like, and is widely applied to most parts of a human body; cancerous tissues, normal tissues, muscles, fat and the like can be accurately distinguished; the ultrasonic and photoacoustic dual-mode imaging system is simple in structure, is not influenced by illumination, is high in sound velocity resolution and signal-to-noise ratio, supports seamless correction and registration of ultrasonic and photoacoustic dual-mode imaging, and promotes clinical application and development of ultrasonic and photoacoustic dual-mode imaging.

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 discloses a tumor irreversible electroporation ablation simulation prediction system, which comprises the following modules: a simulation model geometric structure establishment module, which is used for determining related parameters of a tumor irreversible electroporation ablation operation and a catheter electrode structure, and establishing a geometric structure of a simulation model; the geometric model and numerical model setting module is used for setting a geometric model and a numerical model; respectively constructing a two-electrode plate type three-dimensional finite element multi-physical field simulation model and a three-electrode plate type three-dimensional finite element multi-physical field simulation model for irreversible electroporation ablation of tumors; the data set establishment module is used for respectively performing simulation calculation on the two numerical models constructed by the geometric model and the numerical model setting module; the model training module is used for training the respective data sets of the two numerical models obtained by the data set establishing module by using a random forest regression algorithm; and the simulation prediction module is used for predicting the tumor ablation condition and the damage condition of surrounding normal tissues. The system provided by the invention can accurately predict the tumor ablation condition and the damage condition of surrounding normal tissues.

The invention relates to an intelligent neural navigation system for neurosurgery and a use method thereof.The intelligent neural navigation system comprises an image collecting and processing unit, an intelligent planning unit, a positioning and tracking unit, a visual interaction unit and a data management and updating unit. The optimal operation scheme is selected through operation simulation operation, so that a doctor is helped to master the condition of a patient more clearly, personalized adjustment can be carried out in real time, the operation scheme better fits the actual condition of the patient and the operation habit of the doctor, and the success rate and the quality of an operation are improved. Meanwhile, an optical positioning sensor and an electromagnetic positioning sensor are integrated, accurate position information of the surgical instrument and the area, needing to be treated, of the patient is obtained in real time, operation of the surgical instrument is accurately guided, then it is ensured that the surgical instrument is accurately matched with the preoperative planned path, and mistaken damage to surrounding normal tissue in the surgical process is reduced; and the accuracy and the safety of the operation are improved.

Disclosed are RAS(ON) multi-selective inhibitor compositions and methods of treating RAS protein-related diseases or disorders using an intermittent dosing regimen. RAS(ON) multi-selective inhibitors having tight binding to cyclophilin A (CypA) result in high exposure levels, prolonged tissue retention, and / or slow clearance rates, thereby increasing the risk of inhibition of wild-type RAS in normal tissues. Accordingly, provided herein are methods for the safe and effective dosing of low KD1 RAS(ON) multi-selective inhibitors using an intermittent dosing regimen. Also provided are methods of selecting or identifying such RAS(ON) multi-selective inhibitors suitable for intermittent administration.

The invention discloses a molecular probe for in-vivo copper ion detection and a preparation method and application thereof, the chemical structural formula of the molecular probe is as follows: # imgabs0 #, the molecular probe provided by the invention can specifically respond to copper ions in a tumor subacid environment so as to cause change of an absorption spectrum, and a photoacoustic signal is started so as to detect the copper ions in the tumor subacid environment. Normal tissues and tumor tissues can be accurately distinguished, and accurate detection of the copper ions in the living tumor is realized.

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.

A debridement device for human body pathological tissue, comprising an insertion tube, a rotary cutting head and an operating handle. The insertion tube comprises an inner tube and an outer tube fitted outside the inner tube; an aspiration cavity is formed in the inner tube, and an irrigation cavity is formed between the inner tube and the outer tube; the rotary cutting head comprises a housing and a rotary cutting blade arranged in the housing; the interior of the housing is communicated with the aspiration cavity; a rotary cutting opening exposing the rotary cutting blade is formed on the housing; a notch corresponding to the rotary cutting opening is formed on the outer tube; the operating handle is connected to the insertion tube and the rotary cutting head so as to control the rotary cutting blade to cut human tissue at the rotary cutting opening, suction debris by means of the aspiration cavity, and use the irrigation cavity to flush the position where the rotary cutting head is located. The device can carry out both rotary cutting and aspiration on human body pathological tissue, reduce residues of necrotic tissue, effectively protect surrounding normal tissues and blood vessels, reduce the possibility that a patient requires repeated surgery, and improve the efficiency, effect and safety of minimally invasive therapy.

The invention discloses a method for preparing a methylacryloyl chitosan / gelatin-based hydrogel wound dressing through 3D printing and application, and relates to a method for preparing a hydrogel wound dressing and application. The problems that existing MXene is high in photo-thermal conversion temperature, and bacteria rapidly breed again after near-infrared irradiation is closed are solved. The ZGC composite hydrogel wound dressing integrates multiple functions, can simultaneously realize hemostasis, antibiosis, anti-inflammation, vascularization promotion and cell regeneration, and is especially suitable for infectious wounds. The antibacterial performance can be achieved under the activation of near-infrared light through the dual effects of a photothermal therapy and a photodynamic therapy, and meanwhile, the antibacterial effect can be achieved in cooperation with Zn < 2 + >. The ZGC composite hydrogel wound dressing can be accurately customized and printed through a 3D printing technology according to the shape and depth of a wound, the composite dressing can achieve accurate low-temperature photo-thermal treatment, meanwhile, the continuous release of Zn < 2 + > and the physical antibacterial function of MXene are maintained, normal tissue is protected while bacteria are killed, and the healing rate of an infected wound is remarkably increased.

The present disclosure provides an image processing method, apparatus and device, the method includes: acquiring a visible light image and a fluorescence image corresponding to a designated location inside a target object, where the designated location inside the target object includes diseased tissue and normal tissue; determining a to-be-cut boundary corresponding to the diseased tissue from a to-be-detected image, where the to-be-detected image is the fluorescence image or a fused image of the visible light image and the fluorescence image; and generating a target image, the target image includes the visible light image and the to-be-cut boundary.

The invention discloses an experimental method for relation between cytokine level and tumor immune microenvironment in circulation, which comprises the following steps of: S1, collecting colorectal cancer patient data and normal data for contrast, and preferably screening a gene expression data set from a Gene Expression Omnibus (GEO) database; according to the method, a plurality of gene expression data sets from the GEO database are collected and analyzed, so that differential expression genes between colorectal cancer and normal tissues can be systematically identified, and a solid foundation is provided for subsequent research. The process not only covers batch correction, normalization and batch effect elimination of data, but also visually presents data distribution changes through principal component analysis, ensures the accuracy and reliability of analysis results, confirms that IL6 and IFN gamma are one of the most critical factors affecting the colorectal cancer immune microenvironment, and participate in formation of immune infiltration.

The invention relates to the technical field of image recognition, in particular to a magnetic resonance spectrum imaging automatic positioning method and device, equipment and a medium, and the method comprises the steps: obtaining historical imaging data of different historical brain diseases; constructing a focus recognition module based on historical iconography data; scanning a transection position, a sagittal position and a coronal position of the brain of the target patient to obtain a scanning result; based on the scanning result and a focus recognition model, performing preliminary recognition on the scanning result, and determining the focus level and area of the brain of the target patient; a mode recognition method is adopted to recognize the focus level and area, and the focus parenchyma center is accurately determined; according to the method, scanning is carried out by taking the focus parenchyma center as the single voxel center and taking the focus parenchyma center and normal tissue positions around the focus area as multiple voxels, positioning of magnetic resonance spectrum imaging is realized, a machine model training mode is adopted, the focus positioning speed can be increased, and thus the accuracy of single voxel and multi-voxel spectrum imaging positioning is improved.

The invention provides a dual-targeting carrier material, a preparation method thereof and a preparation method of oleanolic acid nanoparticles wrapped by the dual-targeting carrier material, and belongs to the technical field of medicines. The oleanolic acid targeting nanoparticles are prepared by taking a dual-targeting high-molecular copolymer as a carrier material and adopting an emulsification-solvent evaporation method, so that the oleanolic acid can be protected from being quickly degraded, and the in-vivo circulation time of the oleanolic acid can be prolonged. Meanwhile, targeted delivery of oleanolic acid is realized through a targeted group, the concentration of the drug in tumor tissues is improved, and toxic and side effects on normal tissues are reduced. An MTT method is adopted, the inhibition effect of the oleanolic acid nanoparticles on cell growth is researched, and the result shows that the oleanolic acid targeting nanoparticles have a stronger effect of inhibiting tumor cell proliferation compared with an oleanolic acid raw material medicine.

Surgical marker systems and methods for delineating a lesion margin of a subject are provided. An example system includes a handheld probe device configured to capture an optical coherence tomography (OCT) image and a processor coupled to a memory. The handheld probe device includes a handheld probe including a fiber-optic probe assembly and a marker assembly. The processor is configured to: segment, by a neural network, each pixels of the OCT into different tissue-type categories; generate one or more feature vectors based at least in part on the segmented pixels; determine, by a one-class classifier, a boundary location in the OCT image between a normal tissue and an abnormal tissue of the tissue structure; and control the marker assembly to selectively create a visible label on a tissue location of the subject, the tissue location corresponding to the boundary location.

The invention belongs to the technical field of biological medicine, and particularly discloses an antibody targeting ADAM17 protein and application of the antibody. The invention provides the ADAM17 specific target spot aiming at the malignant tumor of the biliary tract, the ADAM17 is highly expressed in the tumor of the biliary tract and is relatively low in expression in normal tissues, and by intervening the target spot, tumor cells can be killed, and non-specific attack to normal cells can be avoided as much as possible, so that the effectiveness and the safety of treating a patient with the malignant tumor of the biliary tract are improved. The invention also provides an antibody targeting ADAM17 protein and a preparation and screening method thereof, and the antibody can specifically recognize an antigen binding domain of ADAM17, has strong affinity with an ADAM17 antigen, and can be used for treating ADAM17 positive malignant tumors.

The invention belongs to the technical field of physical thermal ablation, and relates to a physical thermal ablation energy regulation and control method based on intelligent feedback, and the method comprises the steps: collecting point-shaped temperature data, impedance data and ultrasonic data, eliminating the asynchronization and heterogeneity problems through space-time alignment, and combining with focus region segmentation, thereby achieving the energy regulation and control of the physical thermal ablation. Discrete data and continuous images are integrated into a voxelization data cube containing space coordinates, physical attributes and semantic tags, then the temperature change rate and the impedance change rate are calculated based on the voxelization data cube, and then a morphological prediction network is fused with multi-modal features to output a voxel-level ablation probability graph. The method comprises the following steps: realizing prospective prediction of an ablation range, ensuring ablation accuracy by morphological deviation through a three-layer parallel regulation and control strategy, preventing and controlling local overheating by temperature gradient, avoiding tissue carbonization by an impedance change rate, and cooperatively deciding through multi-dimensional indexes to solve the contradiction that single regulation and control cannot give consideration to accurate coverage of a focus and protection of normal tissues; and misjudgment caused by abnormity of single data is avoided.

The invention proposes a voxel-level dose distribution prediction method, and the method comprises the steps: obtaining a detection image of a target object when each tracer is independently introduced under the condition that a plurality of tracers are independently introduced into the target object; performing image standardization processing on the detection image corresponding to each tracer agent to obtain a standardized image corresponding to each tracer agent; and taking the standardized images corresponding to the various tracers as input information of a deep learning model, and determining a comprehensive three-dimensional dose prediction result of the target object under the various tracers through the deep learning model. According to the technical scheme, the accuracy of dose prediction in nuclide therapy is improved, full-link automation from image acquisition to dose planning is realized, the generated dose distribution not only meets the clinical requirement of precise coverage of a target region, but also conforms to the radiotherapy principle of normal tissue protection, and reliable technical support is provided for personalized precise radiotherapy.