Hard Exudate Detection with Supervised Contrastive Learning
Overview
A novel supervised contrastive learning framework to optimize hard exudate detection is developed because early detection of hard exudates plays a crucial role in identifying DR, which aids in treating diabetes and preventing vision loss.
Technical name of innovation
Hard Exudate Detection with Supervised Contrastive Learning
Commercialisation opportunities
technology licensing agreement
Problem addressed
The unique characteristics of hard exudates, ranging from their inconsistent shapes to indistinct boundaries, pose significant challenges to existing segmentation techniques.
Innovation
- A novel supervised contrastive learning framework to optimize hard exudate detection is developed.
Key impact
- The technique exhibits its effectiveness and shows potential for computer-assisted hard exudate detection.
- The supervised contrastive learning addresses these challenges effectively by utilizing label information to distinctly separate different classes, therefore managing varying lesion densities and unclear boundaries.
Application
- Early detection of hard exudates plays a crucial role in identifying DR, which aids in treating diabetes and preventing vision loss.
Lingnan University
Lingnan University, a venerable institution in Hong Kong's academic landscape, has a rich heritage that dates back to its founding in Guangzhou in 1888. Known in its earlier years as Lingnan Xuexiao and subsequently as Lingnan University, the institution flourished in the field of higher education until 1952. It was reborn in Hong Kong in 1967 and has since aspired to evolve into a distinguished research-focused liberal arts university for the digital age. Lingnan is committed to excellence in teaching, learning, research, and fostering community ties, aiming for international acclaim.
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