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. © 2010 Springer-Verlag.
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Eichel, J. A., Bizheva, K. K., Clausi, D. A., & Fieguth, P. W. (2010). Automated 3D reconstruction and segmentation from optical coherence tomography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6313 LNCS, pp. 44–57). Springer Verlag. https://doi.org/10.1007/978-3-642-15558-1_4
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