This effort was supported by National Institutes of Health Grant 1R01EY10857-02.
Journal of the Optical Society of America A: Optics, Image Science and Vision
Cataract, Cataract -- Classification
We have developed an autonomous objective classification scheme for degree of nuclear opacification. The algorithm was developed by using a series of color 35-mm slides acquired with a Topcon photo slit-lamp microscope and use of standard camera settings. The photographs were digitized, and first, and second-order gray-level statistics were extracted from within circular regions of the nucleus. Classifications of severity were performed by using these features as input to a neural network. Training versus classification performance was tested by using photographs of different eyes, and test/retest classification reproducibility was evaluated by using paired photographs of the same eyes. We demonstrate good performance of the classifier against subjective assessments rendered by the Wilmer grading system [Invest. Ophthalmol. Visual Sci. 29, 73 (1988)] and markedly better test/retest reproducibility.
D. D. Duncan, O. B. Shukla, S. K. West, and O. D. Schein, "New objective classification system for nuclear opacification," J. Opt. Soc. Am. A 14, 1197-1204 (1997)