Enhancing Vessel Segment Extraction in Retinal Fundus Images Using Retinal Image Analysis and Six Sigma Process Capability Index by Sufian A. Badawi, Maen Takruri, Isam ElBadawi, Imran Ali Chaudhry, Nasr Ullah Mahar, Ajay Kamath Nileshwar, Emad Mosalam

“…Additionally, the existence of a reference dataset for accurate vessel segment images is an essential need for implementing deep learning solutions and an automated system for measuring the vessel biomarkers of several disease diagnoses, especially for optimized quantification of vessel tortuosity or accurate measurement of AV-nicking. This study aimed to present an improved method for skeletonizing and extracting the retinal vessel segments from the 504 images in the AV classification dataset. …”
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RDS-DR: An Improved Deep Learning Model for Classifying Severity Levels of Diabetic Retinopathy by Ijaz Bashir, Muhammad Zaheer Sajid, Rizwana Kalsoom, Nauman Ali Khan, Imran Qureshi, Fakhar Abbas, Qaisar Abbas

“…Cotton wool spots, confined veins in the cranial nerve, AV nicking, and hemorrhages in the optic disc are some of its symptoms, which often appear later. …”
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Retinal changes in patients with idiopathic inflammatory myopathies: A case-control study in the MyoCite cohort by Rachna Aggarwal, R. Naveen, Darpan Thakare, Rohit Shahi, Anamika Kumari Anuja, Ahmad Husain, Maryam Abbasi, Upendra Rathore, Vikas Agarwal, Latika Gupta, Latika Gupta, Latika Gupta, Latika Gupta

“…IIM patients exhibited frequent attenuation of retinal vessels (32.6 vs. 4.3%, p < 0.001), AV nicking (14 vs. 2.2%, p = 0.053), and vascular tortuosity (18.6 vs. 2.2%, p = 0.012), besides decreased visual acuity (53.5 vs. 10.9%, p<0.001) and immature cataracts (34.9 vs. 2.2%, p < 0.001). …”
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