2 results about "T2 weighted" patented technology

The application provides a medical image cross-modality generation method based on double-contrast frequency domain decomposition and adaptive diffusion, which comprises the following steps: acquiring MRI samples and preprocessing, constructing a k-space decomposition and enhancement process, constructing a k-space double-flow adaptive degradation network, and constructing a k-space double-flow adaptive prediction network. Through data enhancement technology and an adaptive Gaussian filter set, different frequency components are separated and enhanced, common edge features are highlighted, and the quality of generated information is improved. By using a residual noise diffusion model, high-resolution images with rich details and high diversity are generated while maintaining smooth areas and large-scale structures of images. By introducing anatomical structure consistency constraints and multi-modality fusion optimization strategies, the complementary information of T1 and T2 weighted MRI is fully utilized, and the generation effect and visual authenticity of the medical image cross-modality generation in a complex scene are significantly improved.

The embodiment of the present application relates to a kind of method and device based on early Alzheimer's disease prediction of lymphoid system characteristics, the method comprises: gathering original sample set, based on 3D-UNet model, first segmentation model is constructed, based on MLP model, first prediction model is constructed;Based on original sample set, first, second data set is constructed;First segmentation model is trained based on first data set;First prediction model is trained based on second data set;After model training ends, the brain DTI image and brain 3D-T2 weighted image of subject are received, and according to brain DTI image, left and right brain ALPS index analysis is carried out based on DTI-ALPS technique, and based on first segmentation model, semantic segmentation is carried out to brain 3D-T2 weighted image, and according to segmentation result, four brain area perivascular space volume fraction analysis is carried out, and using first prediction model, according to two kinds of analysis results, prediction is carried out.The present application can improve processing efficiency, improve prediction accuracy.