The invention discloses an
optic disc atrophy arc weakly supervised segmentation method based on a visual
language model, and belongs to the field of fundus
retina image processing. The method comprises the following steps: constructing a bimodal
encoder comprising a visual feature
encoder and a text
encoder; a visual language multi-
modal feature alignment mechanism is introduced, visual representation learning is guided by using priori knowledge in medical text description, cross-
modal association of images and
lesion semantics is established in a unified feature space, and accurate alignment of visual and text features is realized; generating a focus attention
heat map based on the alignment features, designing an adaptive multi-channel prompt generation network, and automatically mining high-confidence positive and negative prompt points from the
heat map; and taking the generated prompt point as a position guide input segmentation basic model SAM, and realizing fine extraction of the
optic disk atrophy arc boundary under the weak supervision condition of only text description by utilizing the strong zero sample segmentation capability of the SAM.