DeTEC: Detection of touching elongated cells in SEM images

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


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.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - 12th International Symposium, ISVC 2016, Proceedings
EditorsGeorge Bebis, Bahram Parvin, Sandra Skaff, Daisuke Iwai, Richard Boyle, Darko Koracin, Fatih Porikli, Carlos Scheidegger, Alireza Entezari, Jianyuan Min, Amela Sadagic, Tobias Isenberg
Number of pages10
ISBN (Print)9783319508344
StatePublished - 2016
Event12th International Symposium on Visual Computing, ISVC 2016 - Las Vegas, United States
Duration: Dec 12 2016Dec 14 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10072 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference12th International Symposium on Visual Computing, ISVC 2016
Country/TerritoryUnited States
CityLas Vegas

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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