Optic disk and cup joint segmentation network based on improved U-Net
Glaucoma is an irreversible blinding eye disease.The early symptoms of the disease are not obvious,causing many patients to miss the best opportunity for treatment.Fundus photography is a common glaucoma screening method,and the fundus cup-to-disc ratio is one of the important indicators for diagnosing glaucoma.In order to solve the problem of low optic disc and optic cup segmentation accuracy in images,an improved U-Net optic disc and optic cup joint segmentation model CASSP-Net was con-structed.The CBAM attention mechanism and hole space pyramid structure were introduced to further improve the optic disc and optic cup joint segmentation.The accuracy was tested in the Drishti-GS and REFUGE data sets,and achieved good performance of 92.03%and 85.23%on Dice and IoU respectively.
NETL
NSTL
万方数据
