Early detection of glaucoma using fully automated disparity analysis of optic nerve head (ONH) from stereo fundus images

Archie Sharma; Enrique Corona; Sunanda Mitra; Brian S. Nutter

doi:10.1117/12.654019

10 March 2006 Early detection of glaucoma using fully automated disparity analysis of optic nerve head (ONH) from stereo fundus images

Archie Sharma, Enrique Corona, Sunanda Mitra, Brian S. Nutter

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61440H (2006) https://doi.org/10.1117/12.654019
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Early detection of structural damage to the optic nerve head (ONH) is critical in diagnosis of glaucoma, because such glaucomatous damage precedes clinically identifiable visual loss. Early detection of glaucoma can prevent progression of the disease and consequent loss of vision. Traditional early detection techniques involve observing changes in the ONH through an ophthalmoscope. Stereo fundus photography is also routinely used to detect subtle changes in the ONH. However, clinical evaluation of stereo fundus photographs suffers from inter- and intra-subject variability. Even the Heidelberg Retina Tomograph (HRT) has not been found to be sufficiently sensitive for early detection. A semi-automated algorithm for quantitative representation of the optic disc and cup contours by computing accumulated disparities in the disc and cup regions from stereo fundus image pairs has already been developed using advanced digital image analysis methodologies. A 3-D visualization of the disc and cup is achieved assuming camera geometry. High correlation among computer-generated and manually segmented cup to disc ratios in a longitudinal study involving 159 stereo fundus image pairs has already been demonstrated. However, clinical usefulness of the proposed technique can only be tested by a fully automated algorithm. In this paper, we present a fully automated algorithm for segmentation of optic cup and disc contours from corresponding stereo disparity information. Because this technique does not involve human intervention, it eliminates subjective variability encountered in currently used clinical methods and provides ophthalmologists with a cost-effective and quantitative method for detection of ONH structural damage for early detection of glaucoma.

Citation Download Citation

Archie Sharma, Enrique Corona, Sunanda Mitra, and Brian S. Nutter "Early detection of glaucoma using fully automated disparity analysis of optic nerve head (ONH) from stereo fundus images", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61440H (10 March 2006); https://doi.org/10.1117/12.654019

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