MTNet: A combined diagnosis algorithm of vessel segmentation and diabetic retinopathy for retinal images.

ABSTRACT: Medical studies have shown that the condition of human retinal vessels may reveal the physiological structure of the relationship between age-related macular degeneration, glaucoma, atherosclerosis, cataracts, diabetic retinopathy, and other ophthalmic diseases and systemic diseases, and their abnormal changes often serve as a diagnostic basis for the severity of the condition. In this paper, we design and implement a deep learning-based algorithm for automatic segmentation of retinal vessel (CSP_UNet). It mainly adopts a U-shaped structure composed of an encoder and a decoder and utilizes a cross-stage local connectivity mechanism, attention mechanism, and multi-scale fusion, which can obtain better segmentation results with limited data set capacity. The experimental results show that co

SUBMITTER: Liu R 

PROVIDER: S-EPMC9683560 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature