Biomedical subjects
Publications and source records attributed to Jenq-Neng Hwang.
A method is presented for tracking object boundaries in sequential images using an active contour model, based on fuzzy reasoning rule-based control. Evolution of contour segments is controlled by separate processes based on whether the segment is judged to be inside, outside, or near the boundary of the object, leading to robust boundary detection.
PURPOSE: Evaluation of normal and abnormal vascular pattern in the human retina using a novel method: quantitative region-based fractal analysis. METHODS: Binary (black/white) vascular patterns of the human retina originating at the optic disc were obtained by semi-automatic computer processing of digital images from 60-degree fundus fluorescein angiography of 5 normal eyes and 5 eyes with non-proliferative diabetic retinopathy (NPDR). As determined by image resolution, vascular patterns included vessels with diameters >or=50 microm and excluded small vessels and capillaries. The density of linearized (i.e., skeletonized) vascular patterns in the macular region versus paramacular region (termed "region-based" linearized vascular pattern) was quantified with the fractal dimension (D(f)) and confirmed by grid intersection (rho(v)). RESULTS: By region-based quantification, D(f) and rho( v) were significantly higher in the normal macular region than in the NPDR macular region (p = 0.008 and p = 0.019, respectively). However, differences in D(f) and rho(v) between the normal and NPDR paramacular regions were not strongly significant (p = 0.168 and p = 0.337, respectively). CONCLUSIONS: Results from the retrospective analytical study demonstrate the feasibility of using quantitative region-based fractal analysis of early-stage vascular disease in the human retina. The results are encouraging for a broader study of diverse patient populations.