Description:
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.
Subject:
Cataract
Cataract -- Classification
Electrical and Computer Engineering
Raw Url:
http://pdxscholar.library.pdx.edu/do/oai/?metadataPrefix=&verb=GetRecord&identifier=oai:pdxscholar.library.pdx.edu:ece_fac-1116
Source:
Electrical and Computer Engineering Faculty Publications and Presentations
Repository Record Id:
oai:pdxscholar.library.pdx.edu:ece_fac-1116
Record Title:
New Objective Classification System for Nuclear Opacification
https://pdxscholar.library.pdx.edu/ece_fac/117
info:doi/10.1364/JOSAA.14.001197
https://pdxscholar.library.pdx.edu/context/ece_fac/article/1116/viewcontent/new_objective_classification.pdf