OBJECTIVE: To describe a novel approach to measuring anterior chamber angle dimensions and configurations. METHODS: Sixty-nine images were selected randomly from the ultrasound biomicroscopic image database to develop the algorithm. Thirty images were selected for further analyses. The value of each pixel of the 8-bit grayscale ultrasound biomicroscopic images was quantized into 0 (black) or 1 (white), and the edge points outlining the angle were detected and fitted with straight lines. The dimensions and profiles of anterior chamber angles were then measured. RESULTS: The algorithm failed to identify the edge points correctly in 8 (11.6%) of 69 images because of strong background noise. Three basic types of angle configuration were identified based on the derived angle profiles: constant, increasing, and decreasing, which corresponded to flat, bowed forward, and bowed backward iris contours, respectively. The angle measurements demonstrated high correlation with trabecular-iris angle and angle opening distance 500 (calculated as the distance from the corneal endothelium to the anterior iris surface perpendicular to a line drawn at 500 mum from the scleral spur). The strongest association was found between the averaged angle derived from the angle profile and the angle opening distance 500 (r = 0.91). CONCLUSION: The proposed algorithm has high correlations with angle opening distance and trabecular-iris angle with the added advantages of being fully automated, reproducible, and able to capture the characteristic angle configurations. However, good-quality ultrasound biomicroscopic images with high signal-to-noise ratio are required to identify the edge points correctly.
OBJECTIVE: To describe a novel approach to measuring anterior chamber angle dimensions and configurations. METHODS: Sixty-nine images were selected randomly from the ultrasound biomicroscopic image database to develop the algorithm. Thirty images were selected for further analyses. The value of each pixel of the 8-bit grayscale ultrasound biomicroscopic images was quantized into 0 (black) or 1 (white), and the edge points outlining the angle were detected and fitted with straight lines. The dimensions and profiles of anterior chamber angles were then measured. RESULTS: The algorithm failed to identify the edge points correctly in 8 (11.6%) of 69 images because of strong background noise. Three basic types of angle configuration were identified based on the derived angle profiles: constant, increasing, and decreasing, which corresponded to flat, bowed forward, and bowed backward iris contours, respectively. The angle measurements demonstrated high correlation with trabecular-iris angle and angle opening distance 500 (calculated as the distance from the corneal endothelium to the anterior iris surface perpendicular to a line drawn at 500 mum from the scleral spur). The strongest association was found between the averaged angle derived from the angle profile and the angle opening distance 500 (r = 0.91). CONCLUSION: The proposed algorithm has high correlations with angle opening distance and trabecular-iris angle with the added advantages of being fully automated, reproducible, and able to capture the characteristic angle configurations. However, good-quality ultrasound biomicroscopic images with high signal-to-noise ratio are required to identify the edge points correctly.
Authors: Tin A Tun; Mani Baskaran; Shamira A Perera; Anita S Chan; Ching-Yu Cheng; Hla M Htoon; Lisandro M Sakata; Carol Y Cheung; Tin Aung Journal: Graefes Arch Clin Exp Ophthalmol Date: 2014-04-30 Impact factor: 3.117
Authors: Sue-Wei Ho; Mani Baskaran; Ce Zheng; Tin A Tun; Shamira A Perera; Arun K Narayanaswamy; David S Friedman; Tin Aung Journal: Graefes Arch Clin Exp Ophthalmol Date: 2012-09-23 Impact factor: 3.117