Induced electric field distribution prediction method and system based on brain tissue and depth regression

The invention belongs to the field of medical image processing, particularly relates to an induced electric field distribution prediction method and system based on brain tissue and depth regression, and aims to solve the problem that an electric field prediction model under any coil pose cannot be established in the prior art. Electric field prediction cannot be carried out in real time; and the accuracy of a prediction result is low due to systematic deviation. The method comprises the following steps: constructing a deep learning model by taking a 3D attention U-net model as an infrastructure; obtaining an image sampling grid after coil stimulation based on the coil stimulation position, the rotation angle and the image sampling grid before coil stimulation; carrying out T1MRI image resampling, and carrying out brain tissue structure segmentation through a brain tissue segmentation model based on deep learning; and performing real-time induced electric field distribution prediction through the depth regres