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Proceedings Paper

Mixture of learners for cancer stem cell detection using CD13 and H and E stained images
Author(s): Oğuzhan Oğuz; Cem Emre Akbaş; Maen Mallah; Kasım Taşdemir; Ece Akhan Güzelcan; Christian Muenzenmayer; Thomas Wittenberg; Ayşegül Üner; A. Enis Cetin; Rengül Çetin Atalay
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Paper Abstract

In this article, algorithms for cancer stem cell (CSC) detection in liver cancer tissue images are developed. Conventionally, a pathologist examines of cancer cell morphologies under microscope. Computer aided diagnosis systems (CAD) aims to help pathologists in this tedious and repetitive work. The first algorithm locates CSCs in CD13 stained liver tissue images. The method has also an online learning algorithm to improve the accuracy of detection. The second family of algorithms classify the cancer tissues stained with H and E which is clinically routine and cost effective than immunohistochemistry (IHC) procedure. The algorithms utilize 1D-SIFT and Eigen-analysis based feature sets as descriptors. Normal and cancerous tissues can be classified with 92.1% accuracy in H and E stained images. Classification accuracy of low and high-grade cancerous tissue images is 70.4%. Therefore, this study paves the way for diagnosing the cancerous tissue and grading the level of it using H and E stained microscopic tissue images.

Paper Details

Date Published: 23 March 2016
PDF: 16 pages
Proc. SPIE 9791, Medical Imaging 2016: Digital Pathology, 97910Y (23 March 2016); doi: 10.1117/12.2216113
Show Author Affiliations
Oğuzhan Oğuz, Bilkent Univ. (Turkey)
Cem Emre Akbaş, Bilkent Univ. (Turkey)
Maen Mallah, Bilkent Univ. (Turkey)
Kasım Taşdemir, Abdullah Gül Univ. (Turkey)
Ece Akhan Güzelcan, Middle East Technical Univ. (Turkey)
Christian Muenzenmayer, Fraunhofer-Institut für Integrierte Schaltungen (IIS) (Germany)
Thomas Wittenberg, Fraunhofer-Institut für Integrierte Schaltungen (IIS) (Germany)
Ayşegül Üner, Hacettepe Univ. (Turkey)
A. Enis Cetin, Bilkent Univ. (Turkey)
Rengül Çetin Atalay, Middle East Technical Univ. (Turkey)


Published in SPIE Proceedings Vol. 9791:
Medical Imaging 2016: Digital Pathology
Metin N. Gurcan; Anant Madabhushi, Editor(s)

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