Research
2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) | , pp. 4392-4399
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 [9] 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.
We propose SmartKC, a low-cost, smartphone-based keratoconus diagnosis system comprising of a 3D-printed placido’s disc attachment, an LED light strip, and an intelligent smartphone app to capture the reflection of the placido rings on the cornea. Github: microsoft/SmartKC-A-Smartphone-based-Corneal-Topographer: This is the official implementation for the SmartKC project. SmartKC is a smartphone based corneal topographer.