An improved arteriovenous classification method for the early diagnostics of various diseases in retinal image

• Published in: Computer methods and programs in biomedicine Vol. 141; pp. 3 - 9
• Main Authors: Xu, Xiayu, Ding, Wenxiang, Abràmoff, Michael D., Cao, Ruofan
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.04.2017
• Subjects: Arteriovenous classification; Computer-aided diagnostics; Early Diagnosis; Humans; Image analysis; Internal Medicine; Other; Retinal Artery - pathology; Retinal Diseases - diagnosis; Retinal Diseases - pathology; Retinal image; Retinal Vein - pathology; Image analysis; Retinal image; Computer-aided diagnostics; Arteriovenous classification; Computer aided diagnostics
• ISSN: 0169-2607; 1872-7565; 1872-7565
• DOI: 10.1016/j.cmpb.2017.01.007

•This paper proposed an improved pixel-classification based method for artery and vein classification on retinal image.•Intra-image regularization and inter-subject normalization are first used to reduce the image differences in feature space.•Novel features, including first-order and second-order texture features, are introduced to capture the discriminating characteristics.•A high accuracy of 0.923 was achieved on a public database.•The proposed method holds great potential to serve as an early diagnostic tool for various diseases, such as diabetic retinopathy. Retinal artery and vein classification is an important task for the automatic computer-aided diagnosis of various eye diseases and systemic diseases. This paper presents an improved supervised artery and vein classification method in retinal image. Intra-image regularization and inter-subject normalization is applied to reduce the differences in feature space. Novel features, including first-order and second-order texture features, are utilized to capture the discriminating characteristics of arteries and veins. The proposed method was tested on the DRIVE dataset and achieved an overall accuracy of 0.923. This retinal artery and vein classification algorithm serves as a potentially important tool for the early diagnosis of various diseases, including diabetic retinopathy and cardiovascular diseases.