Affiliation:
1. College of Medical Information Engineering, Anhui University of Traditional Chinese Medicine, Hefei 230012, China
2. Artificial Intelligence Research Institute of Hefei Comprehensive National Science Center (Anhui Artificial Intelligence Laboratory), Hefei 230026, China
3. Joint Surgery Department, Hefei First People’s Hospital, Hefei 230061, China
Abstract
Diabetic retinopathy (DR) is a common retinal vascular disease, which can cause severe visual impairment. It is of great clinical significance to use fundus images for intelligent diagnosis of DR. In this paper, an intelligent DR classification model of fundus images is proposed. This method can detect all the five stages of DR, including of no DR, mild, moderate, severe, and proliferative. This model is composed of two key modules. FEB, feature extraction block, is mainly used for feature extraction of fundus images, and GPB, grading prediction block, is used to classify the five stages of DR. The transformer in the FEB has more fine-grained attention that can pay more attention to retinal hemorrhage and exudate areas. The residual attention in the GPB can effectively capture different spatial regions occupied by different classes of objects. Comprehensive experiments on DDR datasets well demonstrate the superiority of our method, and compared with the benchmark method, our method has achieved competitive performance.
Funder
University Synergy Innovation Program of Anhui Province
Subject
General Mathematics,General Medicine,General Neuroscience,General Computer Science
Cited by
26 articles.
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