Feature analysis in slit-lamp image for nuclear cataract diagnosis
Nuclear cataract is the most common type of age-related cataract and it is clinically diagnosed using slit-lamp images. Objective measurement of the features in slit-lamp image is investigated using a computerized software system. The correlation between the features and the nuclear cataract grades is analyzed. Experimental results show that intensity of sulcus, color in the lens and nucleus region, intensity of nucleus, and color in posterior reflex region are the key features for grading nuclear cataract. This study of feature analysis can benefit clinical cataract diagnosis and clinical research. The feature analysis can also be utilized to investigate the performance of different graders and be employed in training of new graders. ©2010 IEEE.
