Computer aided diagnosis for suspect keratoconus detection University of Antwerp Hasselt University
Purpose: To develop a stable and low-cost computer aided diagnosis (CAD) system for early keratoconus detection for clinical use. Methods: The CAD combines a custom-made mathematical model, a feedforward neural network (FFN) and a Grossberg-Runge Kutta architecture to detect clinical and suspect keratoconus. It was applied to retrospective data of 851 subjects for whom corneal elevation and thickness data was available. These data were divided ...