What is it about?
We examine the quantification of retinal blood vessel tortuosity and propose a computer-aided diagnosis system that can be used as a tool for ROP identification. The findings of this study demonstrate the reliability of the proposed method as a computer-aided diagnostic tool that can help medical professionals make an early diagnosis of ROP
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Why is it important?
The goal of this research is to create a diagnostic technique that can discriminate between infants with Plus disease from healthy subjects.
Perspectives
The technique proposed in this research paper is intended for the automated detection of Plus disease which is significant in ROP diagnosis from a prognosis standpoint. The differing opinions among retinal specialists present a significant difficulty in the diagnosis and subsequent management of this condition that threatens vision. Regarding segmentation accuracy and pixel classification, the result obtained by this approach still require improvement. It makes perfect sense that the proposed design has a lot of opportunity for improvisation. Therefore, in the future, we anticipate that this method could be deployed as an adjunct tool to aid clinicians in the early screening of ROP disease.
SIVAKUMAR RAMACHANDRAN
Government Engineering College Wayanad
Read the Original
This page is a summary of: A novel deep learning framework for the identification of tortuous vessels in plus diseased infant retinal images, Intelligent Data Analysis, October 2023, IOS Press,
DOI: 10.3233/ida-220451.
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