228 results about "Cerebral part" patented technology

The invention discloses a multi-modal iconography evaluation method suitable for atrial fibrillation cardiac stroke. The method comprises the following steps: acquiring and preprocessing heart and brain multi-modal image data; carrying out multi-modal image registration on the preprocessed data; feature extraction and fusion are carried out on the registered heart and brain multi-mode image data; performing cross-modal feature alignment and fusion on the heart and brain image data; constructing a heart and cerebral vessel integrated evaluation interaction model based on a graph neural network; predicting the risk of the end-to-end cardiac stroke; according to the multi-modal iconography evaluation method, multi-modal heart image data and multi-modal brain image data are combined, a heart and cerebral vessel integrated evaluation framework is established, image features and clinical data are fused through an artificial intelligence method, and end-to-end stroke risk prediction and evaluation are achieved. According to the method, artificial intelligence and medical technologies are comprehensively utilized, and the accurate cardiac stroke assessment method is provided.

The invention discloses a multi-scale brain tumor segmentation method and system based on adaptive KAN, and a storage medium. The method comprises the following steps: preprocessing three-dimensional brain magnetic resonance imaging data; the preprocessed data are input into an encoder, the encoder comprises a plurality of levels, and each level executes convolution operation to extract local features, executes spatial KAN processing to extract spatial features and downsamples a feature map; the output of the encoder is input into a bottleneck layer, and the bottleneck layer captures a multi-scale global context by using a plurality of parallel expansion convolution branches; the output of the bottleneck layer is input into a decoder, the decoder comprises a plurality of stages, and each stage executes transposing a convolution up-sampling feature map, executes cross-scale gating processing to fuse encoder jump connection features and decoder features, and executes spatial KAN processing to optimize features; and the output of the decoder is input into the output module. According to the method, the problems of low calculation efficiency, poor tumor heterogeneity adaptation, insufficient multi-scale context capture and the like in the existing brain tumor segmentation can be effectively solved.

The invention discloses a hidden multi-mode brain state real-time monitoring and closed-loop intervention system, and relates to the technical field of intelligent wearable equipment. The system comprises a cap body, and further comprises a multi-point electrode array used for collecting EEG (electroencephalogram) signals, EOG (eye movement) signals and EMG (electromyography) signals of a human body; the brain blood oxygen monitoring module is used for monitoring brain blood oxygen saturation; the signal receiving and processing module is used for preprocessing and analyzing data acquired by the multi-point electrode array and the brain blood oxygen monitoring module; the multi-mode stimulation module is used for implementing sensory and nerve stimulation on the user according to a judgment result of the state judgment module so as to intervene in a drowsiness or attention decline state; and the power supply module and the communication unit are used for providing a working power supply for the modules needing power supply in the system and carrying out data communication with external terminal equipment. The system can monitor the waking degree of the user with high precision and carry out closed-loop feedback intervention by various stimulation means.

The invention relates to the technical field of medical image auxiliary diagnosis, in particular to a nuclear magnetic resonance image auxiliary diagnosis method and system based on multi-modal fusion. The method comprises the following steps: step 1, synchronously acquiring a three-dimensional T1 weighted structure image, a T2 weighted fluid attenuation inversion recovery image and diffusion weighted imaging data of a subject, carrying out spatial registration by taking the T1 weighted image as a reference, and executing skull stripping and gray scale standardization; 2, individualized brain region segmentation is carried out based on a brain anatomical map, the lesion sensitivity weight of each modal is calculated for each segmented brain region, and the weight is obtained by quantifying the following parameters; step 3, extracting multi-modal image features in each brain region; and 4, inputting the fusion features of the whole brain region into a multi-task classifier. The standardization and alignment of the multi-mode MRI image in the space and gray level are realized, and the problems of space mismatch and feature interference among different modes are effectively solved.

The invention discloses a cerebral apoplexy focus detection method and system, and belongs to the technical field of medical image detection. Extracting a fusion feature map of the brain image; for each region type, obtaining a representative feature which has the highest similarity with the feature at each pixel point position in the fused feature map in the class prototype set and carries a corresponding region type label, and further determining the region type to which each pixel point position in the fused feature map belongs so as to obtain a corresponding pseudo-label map; the class prototype set comprises representative features of different region types and is obtained in the training process of the system, and feature distribution of different region types in the memory bank is calculated through a Gaussian mixture model; for each region type, sampling is carried out based on feature distribution of the region type, and a plurality of representative features are obtained; the prototype-like set in the cerebral apoplexy detection method has real global context perception ability, can clearly distinguish the focus and various complex background structures, and can accurately realize cerebral apoplexy detection.

The invention relates to the field of small cerebral vessels, in particular to a medical image-based early feature analysis method and system for small cerebral vessels. The method comprises the following steps: acquiring a brain magnetic resonance image data set, preliminarily analyzing brain small vessel local features based on the brain magnetic resonance image data set, and generating a basic brain small vessel feature set; obtaining a clinical parameter set of the patient, analyzing the recessive influence factors according to the clinical parameter set of the patient, and generating a brain small vessel optimized feature set based on the basic brain small vessel feature set and in combination with the recessive influence factors; and performing visual fusion rendering according to the brain small vessel optimized feature set, and generating and outputting a record analysis log. In the process of early feature analysis of small cerebral vessels, doctors are assisted in accurately identifying the enlargement of the gaps around the vessels and simulators thereof, the misjudgment risk is effectively reduced, and the accuracy and reliability of early diagnosis of small cerebral vessel diseases are improved.

The invention discloses a cerebral hemorrhage volume measurement method and related equipment. The method comprises the following steps: acquiring brain medical image data to be measured; inputting the brain medical image data into a three-dimensional segmentation network for cerebral hemorrhage region segmentation to obtain a cerebral hemorrhage region image; identifying a cerebral hemorrhage stage of the cerebral hemorrhage area image according to the cerebral hemorrhage area image; constructing a standard hemorrhage template based on the cerebral hemorrhage stage and the lesion anatomical position in the cerebral hemorrhage area image; performing gradient response analysis based on the feature map of the last convolutional layer in the three-dimensional segmentation network to generate an interpretation map; performing spatial similarity analysis based on the standard bleeding template and the interpretation graph to obtain a consistency score between the standard bleeding template and the interpretation graph; according to the cerebral hemorrhage area image, calculating an initial cerebral hemorrhage volume through a preset dual-path estimation model; and adjusting the fusion weight of the dual-path model according to the consistency score, and determining the target cerebral hemorrhage volume according to the adjusted fusion weight and the initial cerebral hemorrhage volume.

The invention discloses a cerebral hemorrhage heterogeneity quantitative evaluation system based on cyclic cross-attention clustering, and relates to the field of cerebral hemorrhage evaluation, and the system comprises an image segmentation module which is used for carrying out the three-dimensional segmentation of a brain plain-scan CT image through an nnU-NetV2 model, and outputting the binary masks of a hematoma region and an edema region; the feature extraction module is used for extracting high-dimensional pixel features from the mask region and generating an initial feature embedding matrix; the cyclic cross-attention clustering module is used for dynamically updating a clustering center through a multi-scale cyclic EM cross-attention mechanism and executing clustering analysis on the feature embedding matrix; the heterogeneity scoring module is used for calculating information entropy and generating hematoma and edema heterogeneity scores; and the prognosis prediction module is used for predicting the hematoma expansion risk and the neural function outcome through a machine learning model. According to the scheme, objective quantification of cerebral hemorrhage heterogeneity can be realized, and the prediction accuracy of the hematoma expansion risk and the neural function outcome is improved.

The embodiment of the invention discloses a brain operation path determination method and device, equipment, a medium and a medical system. The brain operation path determination method comprises the steps that a brain structure model and at least one target spot of a target user are obtained; based on the brain structure model, determining an information transfer relationship between each nuclear group sub-model and each nerve fiber sub-model; determining a plurality of candidate operation schemes based on the plurality of preset path starting points, the target group sub-model to which the at least one target point belongs and the information transfer relationship; for each candidate operation plan, performing quality evaluation on the candidate operation plan based on a quantitative evaluation model under at least one evaluation dimension, and determining a path quality attribute corresponding to each candidate operation plan; according to the method, at least one target recommended operation scheme is determined based on each path quality attribute, a plurality of candidate paths conforming to nerve conduction characteristics are automatically generated, and an optimal scheme is screened through a quantitative evaluation model, so that the brain tissue injury risk and the operation complexity are effectively reduced while the operation precision is improved.

Methods and systems confirm the treatment focus location of ultrasound energy to be delivered to a patient from a plurality of transducers. The location of focus of treatment ultrasound may be confirmed prior to the start of ultrasound therapy. In some embodiments, ultrasound therapy may comprise delivering treatment ultrasound energy from the treatment ultrasound transducers through the skull to the brain of a patient. Methods for confirming the treatment ultrasound focus location comprise determining receive focus profiles ϕx,v<sub2>i < / sub2>for particular candidate three-dimensional (3D) treatment focus locations and particular assumed ultrasound propagation velocity profiles; performing a pre-treatment (e.g. low-power) ultrasound transmission into the brain of the patient; receiving return signals; and determining the location of treatment focus based at least in part on the received return signals and the receive focus profiles ϕx,v<sub2>i< / sub2>.

Systems and methods for non-invasively measuring intracranial in accordance with embodiments of the invention are illustrated. One embodiment includes a method for estimating an intracranial pressure of a patient, including introducing a tracer into the blood of a patient, recording, using an imaging device, the traversal of the tracer through a brain of the patient as a kinetic curve, estimating a mean transit time (MTT) of the tracer through the brain of the patient based on the kinetic curve, measuring a mean arterial pressure (MAP) of the patient, calculating an intracranial pressure index as MAP−Ck / MTT, where C is a constant to scale proportional relationships based on healthy patient population characteristics, and k is a constant in pressure / time, and providing the intracranial pressure index. In various embodiments, regions of the brain unaffected by transient vascular abnormalities are identified and are used for data collection.

The invention discloses a human brain specific fluid flow direction identification method comprising the following steps: S1, multi-input network model construction: using a decoder to segment a task, and introducing a boundary detection task; high-density lesions and surrounding edema in the medical image are accurately segmented according to the Vi < T > and an attention mechanism; s2, fluid mechanics model construction and parameter setting, focus classification and risk quantification: optimizing time windows of two times of CT scanning; constructing a three-dimensional geometric model of high-density lesions, peripheral edema and normal brain tissue RO I; constructing initial physical field distribution; setting boundary conditions corresponding to a vascular rupture source and a focus drainage area; and dynamically adjusting the time step length based on the flow velocity and the diffusion coefficient. The invention provides a human brain specific fluid flow direction identification method, which combines image high-dimensional features with a multi-physics field coupling model, and reveals the heterogeneity of human brain specific fluid-blood conversion and contrast agent leakage in absorption and peripheral edema expansion modes.

The invention relates to the technical field of neurosurgery navigation, in particular to a neurosurgery brain puncture path accurate planning method and system.The neurosurgery brain puncture path accurate planning method comprises the following steps that by obtaining a preoperative brain function area image and nerve fiber bundle data, a function area range and sensitivity are extracted, a focus and cranial entry point path set is constructed, and a path set is established; the method comprises the steps of analyzing the distance between a path and a functional area and a fiber bundle included angle, calculating a functional interaction risk, dividing path sections and calculating the distances to a blood vessel, a ventricle and the functional area, generating obstacle field intensity and calculating a gradient difference, constructing a risk map, scoring candidate paths, and screening an optimal path to generate a puncture result. The method comprises the following steps: extracting a brain function region range and a fiber bundle direction, introducing a function sensitivity parameter, improving tiny damage identification, calculating obstacle field intensity in a path segmentation manner, forming a gradient, dynamically identifying a high-risk region, grading and screening candidate paths by integrating risk factors, performing function protection and risk reduction, and improving path planning refinement and safety.

The utility model discloses an auxiliary device for achieving simultaneous single-photon and double-photon imaging of the brain and the spinal cord of a mouse, and relates to the technical field of experimental devices.The auxiliary device comprises a brain imaging auxiliary plate, a spine clamping piece and a spinal cord imaging auxiliary plate, a first water containing groove is formed in the middle of the brain imaging auxiliary plate, and a brain imaging auxiliary piece is fixed to the brain of the mouse in an adhesive mode; the spine clamping piece comprises a clamping bottom plate and a pair of clamping plate assemblies, and the clamping plate assemblies can get close to each other in the same direction and get away from each other in opposite directions to clamp and loosen the spine of the mouse; the spinal cord imaging auxiliary plate is detachably arranged on the clamping plate assembly, and a second water containing groove is formed in the middle of the spinal cord imaging auxiliary plate. The brain imaging plate is attached and fixed to the brain of the mouse, the spine clamping piece clamps the spine of the mouse, the spinal cord imaging auxiliary plate is fixed to the spine clamping piece, the spinal cord imaging auxiliary plate is attached to the spine of the mouse, the first water containing groove and the second water containing groove are used for containing water, and therefore groove milling in the skull and the spine of the mouse can be avoided; and the operation difficulty and the operation risk are greatly reduced.

The utility model relates to the technical field of headbands, in particular to a brain protection headband, which is used for surrounding and fixing along the head and comprises a headband body, an application band and an outer band, the application band and the outer band are fixedly connected, and the band surface of the application band is provided with a convex ball used for being applied to the head; the rubber inner pad is used for providing shaping support and is arranged in the headband body, and a third embedding cavity is formed in the rubber inner pad; the sweat-absorbing clamping pad is mounted at the third embedding cavity; according to the brain protection headband, a strip-shaped structure is adopted to replace an existing annular headband, so that the binding force of the headband is convenient to adjust; the shaping capability of the head band can be improved through the rubber inner pad arranged in the head band; in order to improve the wearing comfort, the sweat-absorbing clamping pad is arranged for absorbing sweat; in addition, a convex ball used for being applied to the head is arranged on the belt face of the application belt and can be matched with a strip-shaped structure to adjust the brain pressing force, the adjustability is high, and the application range is wider.

The invention discloses a perfusion imaging method and device for low-rotating-speed imaging equipment, a medium and a product, and relates to the field of medical image processing. The method comprises the following steps: acquiring plain-scan projection data and time sequence projection data of a brain interested body layer; determining a target time decay curve associated with the interested cerebral artery according to the time sequence projection data; determining a difference value between projection data corresponding to each scanning moment in the time sequence projection data and the plain scanning projection data, and taking the difference value as target projection data of the corresponding scanning moment; determining a target independent variable capable of enabling the target projection data and the forward model projection data to meet a difference minimization condition, and determining a perfusion parameter diagram combination based on the target independent variable; the forward model projection data is determined based on a target time decay curve and an independent variable, and the independent variable comprises a cerebral blood flow chart to be optimized and an average passing time chart. According to the invention, the accuracy of the perfusion parameter diagram combination determined based on the projection data acquired by the low-rotating-speed imaging equipment can be improved.

This invention discloses a data processing method and system based on the changing trends of image features, relating to the field of cerebral infarction early warning technology. The data processing method includes: feature extraction: processing image data and modal data separately using feature analysis methods to obtain image features, image feature change data, modal data features, modal data feature change data, and the regions where the features are located. In this invention, image data provides intuitive information about brain structure and lesions, while modal data supplements key features such as hemodynamics, brain tissue electrical activity, and electrical impedance from different physiological dimensions. TCD data can monitor blood flow velocity and vascular resistance in real time, BI data is sensitive to changes in pathological states such as cerebral edema, and EEG data reflects subtle changes in neuronal electrical activity. Through feature extraction and analysis, the combination of multi-source heterogeneous data achieves the correction of image feature changing trends, thereby ensuring the accuracy of data processing.

The invention relates to the technical field of medical instruments, and particularly discloses a puncture fixing device for brain surgery, which comprises a fixed base; fixing mechanisms are mounted on the two sides of the top end of the fixed base, a guide mechanism is jointly mounted between the two ends of the fixed base, and a disinfection mechanism is mounted at the top end of the guide mechanism; through cooperative work of the fixing plate, the fixing groove, the electric telescopic rod, the reinforcing block, the spherical hinge and the fixing clamping plate, the electric telescopic rod can be accurately adjusted according to the shape and size of the head of a patient, the fixing comfort and stability are ensured, and the fixing clamping plate is allowed to be finely adjusted in multiple directions through the design of the spherical hinge; in addition, the pressure sensor embedded in the fixing splint can monitor the clamping force in real time, and the clamping force is automatically adjusted through the controller, so that puncture point deviation caused by micro-motion of the head of the patient in the operation is avoided, the operation risk is reduced, and the safety and the success rate of the operation are improved.

A method for determination of an indicator representative of a change in the brain caused by a demyelinating disease, the method including, for each region of interest of the brain, determining a regional coefficient of one of the following diffusion coefficients: the radial diffusion, the axial diffusion, the mean diffusion, the anisotropy fraction, or a combination of several of these coefficients, the regional coefficients being determined from a diffusion MRI image; determining a number of changed regions, for which a condition relating to the value of the regional diffusion coefficient of each region is satisfied; and determining the indicator in accordance with the number of changed regions.

The invention discloses a three-dimensional surgical risk model reconstruction method based on brain anatomy and a functional atlas, and the method comprises the steps: S1, carrying out the image processing and fine segmentation of a brain MRI image or a DICOM sequence image of a patient, and recognizing a plurality of anatomical structures; s2, establishing a multi-dimensional risk assessment model, and performing quantitative scoring on each brain region from four dimensions of functional importance, structural vulnerability, recovery potential and clinical significance; s3, constructing a continuous three-dimensional risk field based on the risk score, and realizing the propagation of the risk value in the brain tissue based on a Gaussian diffusion model; and S4, based on an improved path planning algorithm, searching an optimal operation path in the three-dimensional risk field to realize risk minimization. The invention further discloses a corresponding system, electronic equipment and a computer readable storage medium.

This disclosure provides an intracranial microneedle implantation assistance method, comprising: determining the positions of each target functional area corresponding to the current microneedle implantation and the positions of each sensitive area contained within each target functional area in a three-dimensional reconstruction model of the brain of the target object; determining a pre-implanted three-dimensional area within a target three-dimensional area composed of all the target functional areas, wherein the pre-implanted three-dimensional area is shaped as a quadrangular prism and the extension direction of the side edges is a preset implantation direction corresponding to the current microneedle implantation; adjusting the position of at least one face and / or at least one side edge of the pre-implanted three-dimensional area by translating it toward the centroid of the pre-implanted three-dimensional area to obtain a final implanted three-dimensional area, wherein the final implanted three-dimensional area does not overlap with any of the sensitive areas.

The adjustor comprises an adjusting belt, a mounting seat, adjusting pieces and the cushion, the adjusting pieces are arranged on the left side and the right side of the mounting seat, the adjusting seat comprises a main body part and a mounting plate arranged on the inner side of the main body part, the adjusting pieces are arranged on the outer side of the main body part, and the cushion is arranged on the mounting plate. The buffer cushion is arranged on the inner surface of the mounting plate; the cushion pad is made of one or more of plastic, silica gel and soft rubber. The buffering cushion has the effects of force unloading and shock absorption, and can reduce or eliminate impact force when being impacted in the riding process, so that a certain effect of protecting the head is achieved, the damage of impact to the head is reduced, the probability of cerebral concussion caused by collision of the brain of a wearer is reduced, and the safety of the wearer is improved. And the use safety of the regulator is greatly improved. In addition, due to the certain thickness of the buffering pad, the wearing comfort and the buffering effect can be improved, and the practicability is high.

The invention discloses a cerebral infarction risk early warning method and system based on an image feature change trend, and relates to the technical field of cerebral infarction early warning. The cerebral infarction risk early warning method comprises the steps of feature extraction, wherein image data and modal data are processed through a feature analysis method, and image features, image feature change data, modal data features, modal data feature change data and regions where the features are located are obtained; the image data provides visual information of a brain structure and a focus, the modal data supplements key features such as hemodynamics, brain tissue electrical activity and electrical impedance from different physiological dimensions, the TCD data can monitor blood flow velocity and vascular resistance in real time, and the BI data is sensitive to change of pathological states such as encephaledema. The EEG data reflects the subtle change of the electrical activity of neurons, and the image feature change trend is corrected through feature extraction and analysis and combination of multi-source heterogeneous data, so that the accuracy of cerebral infarction risk early warning is ensured.

Provided are systems, methods, and devices for providing mediation of a traumatic brain injury. Systems may include an interface, processing devices, and a controller. The interface is configured to obtain measurements from a brain of a user with a traumatic brain injury. A first processing device is configured to generate multiple brain state parameters characterizing one or more features of a brain state of the user. A second processing device is configured to generate models of the brain of the user based on the plurality of brain state parameters and the plurality of measurements, and determine, using the models and training data comprising one or more mediation data points, a mediation procedure for reducing one or more symptoms of the traumatic brain injury. The mediation procedure is provided to one or more entities, and one or more control signals are generated by the controller based on the mediation procedure.

An artificial intelligence (Al) engine is trained on a plurality of annotated magnetic resonance (MR) images of a patient's brain. A plurality of MR images of a patient's head is provided. For each MR image in the plurality of provided MR images, the Al engine detects a plurality of edges of the brain and determine a biparietal diameter (BP) value, detects a plurality of frontal horn edges, and detects a plurality of occipital horn edges. A correction module determines that at least one detected edge is associated with a non -ventricular body and updates the edge to correspond to the applicable horn. The Al engine determines a frontal horn diameter (F) value, and a occipital horn diameter (O) value. An indication module provides an indication on abnormal dilation of the patient's brain ventricles based on a maximum F value, a maximum O value, and the maximum BP value.

A method of detecting changes in blood flow in a head of a subject includes measuring a value of a parameter of a cardiac bioelectrical signal at a scalp area of the subject relative to a reference cardiac bioelectrical signal. The method also includes comparing the value of the measured parameter with a predetermined value of the parameter to determine any change in blood flow in the head of the subject. The determined change can be used to detect changes in perfusion in the brain of a subject for example, as a result of anti-coagulation medication used to dissolve a clot in a blood vessel of the brain of a subject who has experienced ischaemic stroke.

The invention belongs to the technical field of medical instruments, and particularly discloses an intracranial pressure monitoring and external ventricular automatic drainage regulation and control device which comprises a sensing module, a lifting module and a control module. The sensing module comprises a pressure sensor and a blood pressure monitor, the pressure sensor is used for monitoring intracranial pressure data, and the blood pressure monitor is used for monitoring blood pressure data; the lifting module is provided with a mounting part, the mounting part is used for mounting a drainage bottle, and the drainage bottle is connected with the brain of a patient through a catheter; the control module is used for periodically executing the following operations: performing statistical analysis based on the intracranial pressure data and the blood pressure data to obtain multiple statistical values; and regulating and controlling the height of the mounting piece in the lifting module based on the plurality of statistical values. According to the device, monitoring data are obtained through the pressure sensor and the blood pressure monitor, statistical analysis and regulation are conducted through the control module, the state of a patient can be obtained in time, automatic regulation is conducted when the intracranial pressure of the patient is too low or too high, and the height of the drainage bottle is efficiently regulated.

The application discloses a kind of intracranial charged dispersion electric stimulation devices for depression, belong to transcranial electric stimulation field;A kind of intracranial charged dispersion electric stimulation devices for depression includes hat shell and electric stimulation main body, first round hole is opened in hat shell, electric stimulation main body includes the power supply box of cooperation installation with first round hole, at least six elastic metal supports are arranged around power supply box and are distributed in circumference, two elastic metal supports end portions located in front and back are equipped with two permanent magnet fixed slots, and two magnetic pole opposite permanent magnets are fixed respectively;The electrode assembly is installed in the end portion of the remaining multiple elastic metal supports located in left and right sides, and electrode piece capable of acting on brain is arranged on electrode assembly;Stimulating current can be generated between multiple electrode pieces, and current occurs charged dispersion in intracranial under the action of magnetic field generated by magnetic pole, and more parts such as amygdala, hippocampus can be stimulated.

The invention relates to the technical field of teaching models, in particular to a spliced mold capable of achieving lamplight demonstration of brain nerves and blood vessels and a control system. The system is composed of a plurality of physical modules which can be spliced and separated, and independent light-emitting units representing nerves and blood vessels are embedded in the modules. The system core comprises a monitoring module for monitoring the connection state of the module, a database for storing preset light sequences and voice explanation behaviors, an interaction interface for receiving user instructions and a control module serving as a control center. During working, the control module drives the corresponding light-emitting units to work in sequence according to a behavior instruction triggered by a user so as to dynamically simulate neural signals or blood flow, and can respond to splicing state changes of the modules in real time: when the modules are separated, internal light flow can be independently and continuously demonstrated; after the modules are spliced, the whole optical flow is recovered from the breakpoint. The system realizes unification of brain structure and function dynamic demonstration, local depth observation and overall process teaching.

The invention relates to a cerebral cortex metabolism visualization method and system. The method comprises the steps of obtaining a first functional image and a structure image of the brain of a target patient; based on the target neural network model, performing denoising processing on the first functional image to obtain a second functional image; wherein the target neural network model is obtained by training an initial neural network model based on a sample set, the sample set comprises multiple groups of samples, and each group of samples comprises a first functional image sample and a structure image sample of the brain of a sample patient; generating a three-dimensional grid model of the cerebral cortex according to the structure image; and mapping the metabolic information in the second functional image into the three-dimensional grid model, and visualizing the metabolic information in the three-dimensional grid model. By adopting the method, accurate correspondence and visual fusion expression of the brain anatomical structure information and metabolism information of the target patient can be realized, and the observation efficiency of a doctor is improved.