Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

Journal: Translational vision science & technology

PMID: 39847377

Abstract

PURPOSE: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.

Authors

Rehana Khan

Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, India.
Vinod Maseedupally

School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Kaveri A Thakoor
Rajiv Raman

Shri Bhagwan Mahavir Vitreoretinal Services, Sankara Nethralaya, Chennai, Tamil Nadu, India.
Maitreyee Roy

School of Optometry and Vision Science, UNSW Sydney, Sydney, NSW, 2052, Australia. maitreyee.roy@unsw.edu.au.

Keywords

Adult Aged Anemia Deep Learning Female Fundus Oculi Hemoglobins Humans Image Processing, Computer-Assisted India Male Middle Aged Neural Networks, Computer Resource-Limited Settings Retina ROC Curve Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (39847377)

Noninvasive Anemia Detection and Hemoglobin Estimation from Retinal Images Using Deep Learning: A Scalable Solution for Resource-Limited Settings.

Abstract

Authors

Keywords

External Resources

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