5 results about "Brain White Matter" patented technology

The application belongs to the field of brain white matter fiber track prediction, and relates to a brain white matter fiber track prediction method and system based on a pre-trained basic model. The method adopts an MAE architecture, and performs self-supervised pre-training on large-scale brain fiber track data through a mask-reconstruction mechanism to learn global topology and local geometric features of neural fibers. In the training stage, a hybrid progressive mask strategy is introduced. In the initial stage of the model, continuous segment masks are mainly used, and gradually transition to random point masks, so as to realize hierarchical learning of structural patterns and robust expression of features. After pre-training is completed, the model is fine-tuned, so that only the input of the two end point coordinates of the fiber can reconstruct and predict the intermediate track, and the fiber path inference based on the end point is realized. In the fine-tuning stage, the encoder structure is kept stable, the decoder is guided by the end point features to generate complete tracks conforming to the structural distribution of the brain white matter fiber, and the technical problems existing in the prior art are solved.

This invention discloses a method, apparatus, device, storage medium, and program product for generating a head model. The key features include receiving and verifying original 3D T1-weighted image data and an original 3D mesh model; performing tissue segmentation based on the verified 3D T1-weighted image data and the original 3D T1-weighted image data to obtain gray matter masks, white matter masks, scalp masks, and skull masks; performing topological repair on the gray matter and white matter masks to obtain a brain mask; converting the scalp mask, skull mask, and brain mask into scalp mesh models, skull mesh models, and brain mesh models, respectively; calculating and applying the spatial transformation matrix from the verified 3D mesh model to the scalp mesh model; and performing spatial registration and fusion of the scalp mesh model, skull mesh model, and brain mesh model to obtain the head model. The advantages are that it effectively improves the efficiency, accuracy, and robustness of head model generation and has good cross-platform deployment capabilities.

The application discloses a kind of infant brain white matter injury cognitive prognosis evaluation method, system and device, it is related to medical technical field, the method includes obtaining the T1 weighted imaging and diffusion tensor image of the brain of infant to be evaluated;The local white matter injury area is outlined on T1 weighted image, and binary individual lesion mask is generated;The diffusion tensor image is preprocessed, and partial anisotropy map is generated;Based on individual lesion mask and diffusion tensor image, the lesion volume involving fiber bundle and white matter structure disconnection score are calculated in parallel;The lesion volume involving fiber bundle and white matter structure disconnection score are input into pre-trained decision tree model, according to the preset determination rule, the evaluation result of the risk of infant cognitive development delay is output;The method provides new quantitative index for PWML dominant lesion, can be derived to conventional MRI image and analyzed, without acquiring DTI data, and provides a new solution for early evaluation of prognosis.

This invention provides a brain tissue equivalent material for medical imaging equipment and its preparation method, belonging to the technical field of tissue equivalent materials. The brain tissue equivalent material of this invention comprises the following raw materials in the indicated mass fractions: 20-35% bisphenol A epoxy resin, 10-15% octyl glycidyl ether, 1-5% urea, 1-5% calcium carbonate, 1-5% sodium dihydrogen phosphate, 1-5% dipotassium hydrogen phosphate, 15-35% polyethylene, 15-25% methyl methacrylate, and 5-15% trimethylhexanediamine. The CT value of the brain tissue equivalent material of this invention is highly consistent with that of real brain tissue, successfully covering the typical range of gray and white matter. The brain tissue equivalent material exhibits excellent wide-spectrum attenuation characteristics; within the commonly used energy range of 60-200 keV in clinical CT equipment, the deviation of the X-ray attenuation coefficient from the target brain tissue material is controlled within 5%, demonstrating excellent spectral stability and simulation accuracy.