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2016 | OriginalPaper | Chapter

DeTEC: Detection of Touching Elongated Cells in SEM Images

Authors : A. Memariani, C. Nikou, B. T. Endres, E. Bassères, K. W. Garey, I. A. Kakadiaris

Published in: Advances in Visual Computing

Publisher: Springer International Publishing

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Abstract

A probabilistic framework using two random fields, DeTEC (Detection of Touching Elongated Cells) is proposed to detect cells in scanning electron microscopy images with inhomogeneous illumination. The first random field provides a binary segmentation of the image to superpixels that are candidates belonging to cells, and to superpixels that are part of the background, by imposing a prior on the smoothness of the texture features. The second random field selects the superpixels whose boundaries are more likely to form elongated cell walls by imposing a smoothness prior onto the orientations of the boundaries. The method is evaluated on a dataset of Clostridium difficile cell images and is compared to CellDetect.

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Metadata
Title
DeTEC: Detection of Touching Elongated Cells in SEM Images
Authors
A. Memariani
C. Nikou
B. T. Endres
E. Bassères
K. W. Garey
I. A. Kakadiaris
Copyright Year
2016
Book
Advances in Visual Computing

Print ISBN: 978-3-319-50834-4

Electronic ISBN: 978-3-319-50835-1

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-50835-1_27

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