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DL-Assisted ROP Screening Technique

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Biomedical Engineering Systems and Technologies (BIOSTEC 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1710))

Abstract

Retinopathy of Prematurity (ROP) is the most common cause of visual impairment among premature babies throughout the world. The consequence of ROP impairment can be minimized by performing suitable screening and treatment. However, due to deficiency of health care resources, many of these premature infants remain unidentified after birth. As a result, ROP-induced visual impairment is much more prevalent in these babies. We propose a robust and intelligent approach based on deep artificial intelligence and computer vision to automatically recognise the optical disk (OD) and retinal blood vessels and categorise the severe severity (Zone-1) of ROP patients in this study. We report empirical evidence using premature infant retina images from a nearby hospital to evaluate and validate the proposed approach. The YOLO-V5 prediction model identifies the OD from premature infants retina images, according to our results. Furthermore, the preterm infants’ fundus images were perfectly segmented by the computer vision-based system, which effectively separated the retinal vessels. Our system is able to obtain an accuracy of 82.5% in the Zone-1 occurrence of ROP.

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Notes

  1. 1.

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Acknowledgements

We acknowledge key insights received from Prof. P. K. Kalra in discussion that we have done related to this work.

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Authors and Affiliations

  1. Khosla School of Information Technology, Indian Institute of Technology Delhi, New Delhi, India

    Vijay Kumar & Kolin Paul

  2. Department of Computer Science and Engineering, Indian Institute of Technology Delhi, New Delhi, India

    Het Patel & Kolin Paul

  3. Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences Delhi, New Delhi, India

    Shorya Azad, Abhidnya Surve & Rohan Chawla

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  1. Vijay Kumar
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  2. Het Patel
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  3. Shorya Azad
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  4. Kolin Paul
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  5. Abhidnya Surve
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  6. Rohan Chawla
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Corresponding author

Correspondence to Vijay Kumar .

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Editors and Affiliations

  1. INSA-Lyon, Villeurbanne, France

    Claudine Gehin

  2. FEMTO-ST, Besancon, France

    Bruno Wacogne

  3. Toronto Metropolitan University, Toronto, ON, Canada

    Alexandre Douplik

  4. University of Vienna, Vienna, Austria

    Ronny Lorenz

  5. Charles River Analytics, Inc., Cambridge, MA, USA

    Bethany Bracken

  6. University of Lisbon, Lisbon, Portugal

    Cátia Pesquita

  7. Instituto de Telecomunicações, Aveiro, Portugal

    Ana Fred

  8. Universidade Nova de Lisboa, Caparica, Portugal

    Hugo Gamboa

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Kumar, V., Patel, H., Azad, S., Paul, K., Surve, A., Chawla, R. (2022). DL-Assisted ROP Screening Technique. In: Gehin, C., et al. Biomedical Engineering Systems and Technologies. BIOSTEC 2021. Communications in Computer and Information Science, vol 1710. Springer, Cham. https://doi.org/10.1007/978-3-031-20664-1_13

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  • DOI: https://doi.org/10.1007/978-3-031-20664-1_13

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