SmartKC++: Improving Performance of Smartphone-Based Corneal Topographers

Vaibhav Ganatra, Siddhartha Gairola, Pallavi Joshi, Anand Balasubramaniam, Kaushik Murali, Arivunithi Varadharajan, Bellamkonda Mallikarjuna, Nipun Kwatra, Mohit Jain; Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025, pp. 4392-4399

Abstract

Keratoconus an ocular condition marked by progressive corneal thinning and outward bulging presents diagnostic challenges due to the high cost and lack of portability in conventional corneal topographers. These limitations restrict accessibility for many necessitating affordable and mobile alternatives. Innovations like SmartKC offer a low-cost and portable alternative however there still remains some gaps in performance when compared to commercial topographers. In this paper we introduce SmartKC++ a series of innovative methodological improvements to the image processing pipeline of SmartKC aimed at significantly enhancing its diagnostic precision and reliability. Our comprehensive evaluation on a dataset comprising 303 eye images reveals that SmartKC++ boosts the accuracy of automated keratoconus diagnosis by 7.69% relative to SmartKC.

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[bibtex]
@InProceedings{Ganatra_2025_WACV, author = {Ganatra, Vaibhav and Gairola, Siddhartha and Joshi, Pallavi and Balasubramaniam, Anand and Murali, Kaushik and Varadharajan, Arivunithi and Mallikarjuna, Bellamkonda and Kwatra, Nipun and Jain, Mohit}, title = {SmartKC++: Improving Performance of Smartphone-Based Corneal Topographers}, booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)}, month = {February}, year = {2025}, pages = {4392-4399} }