Automatic detection of microaneurysms and hemorrhages in digital fundus images.

Journal of Digital Imaging
Giri Babu KandeP Venkata Subbaiah

Abstract

An efficient approach for automatic detection of red lesions in ocular fundus images based on pixel classification and mathematical morphology is proposed. Experimental evaluation of the proposed approach demonstrates better performance over other red lesion detection algorithms, and when determining whether an image contains red lesions the proposed approach achieves a sensitivity of 100% and specificity of 91%.

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Citations

Jun 12, 2013·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Bálint Antal, András Hajdu
Nov 14, 2015·Computer Methods and Programs in Biomedicine·Ji-Jiang YangQing Wang
May 14, 2016·Computers in Biology and Medicine·Jyoti Prakash Medhi, Samarendra Dandapat
Feb 18, 2016·IEEE Transactions on Medical Imaging·Mark J J P van GrinsvenClara I Sanchez
Aug 9, 2017·Journal of Digital Imaging·Arati Manjaramkar, Manesh Kokare
Dec 7, 2017·Journal of Digital Imaging·Sajib Kumar SahaYogesan Kanagasingam
Feb 25, 2015·Journal of Healthcare Engineering·Mingui SunWenyan Jia
Oct 28, 2017·Biomedical Engineering Online·Zhitao XiaoChunyan Shan
Apr 26, 2019·European Journal of Ophthalmology·Shilpa Joshi, P T Karule
Feb 3, 2021·Journal français d'ophtalmologie·A BilalS Mazhar
Nov 21, 2019·Computers in Biology and Medicine·Gabriel Tozatto ZagoEvandro Ottoni Teatini Salles

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