Deep Learning Assisted Plus Disease Screening of Retinal Image of Infants

Vijay Kumar, Vatsal Agrawal, Shorya Azad, Kolin Paul, Kolin Paul

2023

Abstract

Retinopathy of Prematurity (ROP) is the leading cause of blindness in premature infants in developing countries. The international classification of ROP (ICROP) classifies ROP based on location, severity, and stage. Plus disease is a crucial feature in ROP classification. Plus is the most severe form of vascular dilatation and tortuosity, and it causes severe ROP and visual loss if untreated. Despite decades of research, identifying and quantifying Plus diseases is challenging. Understanding and detecting Plus in ROP patients can help ophthalmologists provide better treatment, restoring vision to many infants with severe ROP. Hence, we have proposed a robust Deep Learning-assisted framework for Blood Vessels map generation and analysis that may effectively address the issue related to Plus disease screening and monitoring. We have extensively studied various methods for computing and locating different blood vessel map features such as vessel branch point, vessel width, vessel skeleton/centre-line, vessel segment tortuosity, etc. Additionally, we divided the branches into two levels based on the width of the branches. For our investigations, we have used both local and public databases. This work also includes a detailed analysis of these datasets’ vascular feature and their level. To the best of our knowledge, none of the publicly available models could independently classify branches and/or analyse the tortuousness based on the parent and child relationship of branches. For Plus, pre-Plus, and Healthy infants, the average tortuosity index is 1.959, 1.1530, and 1.126, and the percentage of vessels severely infected is 44%, 30%, and 20%, respectively. Moreover, our algorithm recognises and analyses many vessels. The precision of many parameters is remarkable.

Paper Citation

in Harvard Style

Kumar V., Agrawal V., Azad S. and Paul K. (2023). Deep Learning Assisted Plus Disease Screening of Retinal Image of Infants. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF; ISBN 978-989-758-631-6, SciTePress, pages 538-545. DOI: 10.5220/0011803700003414

in Bibtex Style

@conference{healthinf23,
author={Vijay Kumar and Vatsal Agrawal and Shorya Azad and Kolin Paul},
title={Deep Learning Assisted Plus Disease Screening of Retinal Image of Infants},
booktitle={Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF},
year={2023},
pages={538-545},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011803700003414},
isbn={978-989-758-631-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2023) - Volume 5: HEALTHINF
TI - Deep Learning Assisted Plus Disease Screening of Retinal Image of Infants
SN - 978-989-758-631-6
AU - Kumar V.
AU - Agrawal V.
AU - Azad S.
AU - Paul K.
PY - 2023
SP - 538
EP - 545
DO - 10.5220/0011803700003414
PB - SciTePress