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Exudate Extraction From Fundus Images Using Machine Learning

Exudate Extraction From Fundus Images Using Machine Learning
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Author(s): Sindhu P. Menon (Jain College of Engineering and Technology, India)
Copyright: 2022
Volume: 11
Issue: 1
Pages: 16
Source title: International Journal of Biomedical and Clinical Engineering (IJBCE)
Editor(s)-in-Chief: Natarajan Sriraam (M.S. Ramaiah Institute of Technology, India)
DOI: 10.4018/IJBCE.290388

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Abstract

Patients suffering from diabetes have to bear several other disorders due to this. Diabetic Retinopathy is one such disorder which affects diabetic patients. This disorder affects the patient’s eye leading to permanent blindness if left untreated. Another disorder is exudates in which lipid residues leak out from damaged capillaries. It appears as yellow flecks. Hard exudates can lead to life threatening disorders. Detecting Hard exudates help the Ophthalmologist to diagnose the severity of the patient’s condition and in turn help in better medication. This paper presents a method to adjust the contrast of the image which in turn helps in detecting the hard exudates which can be used for further processing. In this work, initially Otsu algorithm is applied and then compared with Machine Learning techniques due to the disadvantage of Otsu.

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