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Software Tools and Algorithms for Biological Systems pp 413–424Cite as

Histopathology Tissue Segmentation by Combining Fuzzy Clustering with Multiphase Vector Level Sets

Part of the Advances in Experimental Medicine and Biology book series (AEMB,volume 696)

Abstract

High resolution, multispectral, and multimodal imagery of tissue biopsies is an indispensable source of information for diagnosis and prognosis of diseases. Automatic extraction of relevant features from these imagery is a valuable assistance for medical experts. A primary step in computational histology is accurate image segmentation to detect the number and spatial distribution of cell nuclei in the tissue, along with segmenting other structures such as lumen and epithelial regions which together make up a gland structure. This chapter presents an automatic segmentation system for histopathology imaging. Spatial constraint fuzzy C-means provides an unsupervised initialization. An active contour algorithm that combines multispectral edge and region informations through a vector multiphase level set framework and Beltrami color metric tensors refines the segmentation. An improved iterative kernel filtering approach detects individual nuclei centers and decomposes densely clustered nuclei structures. The obtained results show high performances for nuclei detection compared to the human annotation.

Keywords

  • Active Contour
  • Spatial Constraint
  • Gleason Grade
  • Histopathology Image
  • Geodesic Active Contour

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Notes

  1. 1.

    Histopathology imagery provided by Michael Feldman (Department of Surgical Pathology, University of Pennsylvania) and ground truth from Anant Madabhushi (Rutgers).

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Authors and Affiliations

  1. Department of Computer Science, University of Missouri-Columbia, Columbia, MO, 65211, USA

    Filiz Bunyak

Authors
  1. Filiz Bunyak
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  2. Adel Hafiane
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  3. Kannappan Palaniappan
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Corresponding author

Correspondence to Filiz Bunyak .

Editor information

Editors and Affiliations

  1. Dept. Computer Science, University of Georgia, Athens, 30602-7404, Georgia, USA

    Hamid R. Arabnia

  2. , Department of Computer Science, Lamar University, Beaumont, 77710, Texas, USA

    Quoc-Nam Tran

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Bunyak, F., Hafiane, A., Palaniappan, K. (2011). Histopathology Tissue Segmentation by Combining Fuzzy Clustering with Multiphase Vector Level Sets. In: Arabnia, H., Tran, QN. (eds) Software Tools and Algorithms for Biological Systems. Advances in Experimental Medicine and Biology, vol 696. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-7046-6_41

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