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Proceedings Paper

Convolution neural network for contour extraction of corneal endothelial cells
Author(s): Saya Katafuchi; Motohide Yoshimura
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Paper Abstract

The corneal endothelial cells exist on the human’s cornea. To extract every cell contour from them is indispensable for the assessment of cell condition. However, it is difficult to distinguish the contour of large cells from the cytoplasm because of their homogeneity of gray scale pattern. In this paper, we construct the CNNs for the precise cell extraction regardless to scale of the cell. We utilize software library Caffe as a Deep Learning framework. We show the effectiveness of CNNs for the contour extraction of corneal endothelial cells.

Paper Details

Date Published: 14 May 2017
PDF: 7 pages
Proc. SPIE 10338, Thirteenth International Conference on Quality Control by Artificial Vision 2017, 103380L (14 May 2017); doi: 10.1117/12.2264430
Show Author Affiliations
Saya Katafuchi, Univ. of Nagasaki (Japan)
Motohide Yoshimura, Univ. of Nagasaki (Japan)


Published in SPIE Proceedings Vol. 10338:
Thirteenth International Conference on Quality Control by Artificial Vision 2017
Hajime Nagahara; Kazunori Umeda; Atsushi Yamashita, Editor(s)

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