NDLI: Automatic 3D change detection for glaucoma diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Lu Wang Kallem, V. Bansal, M. Eledath, J. Sawhney, H. Pearson, D.J. Stone, R.A.
Copyright Year	2014
Description	Author affiliation: Sch. of Med., Scheie Eye Inst., Univ. of Pennsylvania, Philadelphia, PA, USA (Pearson, D.J.; Stone, R.A.) \|\| SRI Int., Princeton, NJ, USA (Lu Wang; Kallem, V.; Bansal, M.; Eledath, J.; Sawhney, H.)
Abstract	Important diagnostic criteria for glaucoma are changes in the 3D structure of the optic disc due to optic nerve damage. We propose an automatic approach for detecting these changes in 3D models reconstructed from fundus images of the same patient taken at different times. For each time session, only two uncalibated fundus images are required. The approach applies a 6-point algorithm to estimate relative camera pose assuming a constant camera focal length. To deal with the instability of 3D reconstruction associated with fundus images, our approach keeps multiple candidate reconstruction solutions for each image pair. The best 3D reconstruction is found by optimizing the 3D registration of all images after an iterative bundle adjustment that tolerates possible structure changes. The 3D structure changes are detected by evaluating the reprojection errors of feature points in image space. We validate the approach by comparing the diagnosis results with manual grading by human experts on a fundus image dataset.
Sponsorship	IEEE Comput. Soc.
Starting Page	401
Ending Page	408
File Size	4149269
Page Count	8
File Format	PDF
ISBN	9781479949854
DOI	10.1109/WACV.2014.6836072
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Cameras Optical imaging Solid modeling Image reconstruction Adaptive optics Retina
Content Type	Text
Resource Type	Article

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