METHOD AND SYSTEM FOR CONSTRUCTING SEMI-SUPERVISED IMAGE SEGMENTATION FRAMEWORK

A method for constructing a semi-supervised image segmentation framework, the method comprising: constructing a semi-supervised image segmentation framework which comprises a student model, a teacher model and a discriminator (S1); acquiring a marked MRI image and a corresponding gold standard thereof, so as to calculate a supervised segmentation loss; acquiring an original unmarked MRI image and an unmarked MRI noise image that is obtained after combining the original unmarked MRI image with pre-set Gaussian distribution noise, so as to obtain a corresponding student segmentation probability result graph and a corresponding teacher segmentation probability result graph, then respectively covering the original unmarked MRI image with same, and generating a student segmentation area and a teacher segmentation area and transmitting same together to the discriminator for similarity comparison, so as to calculate a consistency loss; and obtaining the total segmentation loss according to the supervised segmentatio