Automated 3D reconstruction and segmentation from optical coherence tomography

Authors:
Justin A. Eichel;Kostadinka K. Bizheva;David A. Clausi;Paul W. Fieguth
Affiliations:
Systems Design Engineering, University of Waterloo, Canada;Department of Physics and Astronomy, University of Waterloo, Canada;Systems Design Engineering, University of Waterloo, Canada;Systems Design Engineering, University of Waterloo, Canada
Venue:
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Year:
2010

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Abstract

Ultra-High Resolution Optical Coherence Tomography is a novel imaging technology that allows non-invasive, high speed, cellular resolution imaging of anatomical structures in the human eye, including the retina and the cornea. A three-dimensional study of the cornea, for example, requires the segmentation and mutual alignment of a large number of two-dimensional images. Such segmentation has, until now, only been undertaken by hand for individual two-dimensional images; this paper presents a method for automated segmentation, opening substantial opportunities for 3D corneal imaging and analysis, using many hundreds of 2D slices.