Novel approach for anterior chamber angle analysis: anterior chamber angle detection with edge measurement and identification algorithm (ACADEMIA).

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.