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Segmenting Neuroblastoma Tumor Images and Splitting Overlapping Cells Using Shortest Paths between Cell Contour Convex Regions

  • Siamak Tafavogh
  • Karla Felix Navarro
  • Daniel R. Catchpoole
  • Paul J. Kennedy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7885)

Abstract

Neuroblastoma is one of the most fatal paediatric cancers. One of the major prognostic factors for neuroblastoma tumour is the total number of neuroblastic cells. In this paper, we develop a fully automated system for counting the total number of neuroblastic cells within the images derived from Hematoxylin and Eosin stained histological slides by considering the overlapping cells. We finally propose a novel multi-stage cell counting algorithm, in which cellular regions are extracted using an adaptive thresholding technique. Overlapping and single cells are discriminated using morphological differences. We propose a novel cell splitting algorithm to split overlapping cells into single cells using the shortest path between contours of convex regions.

Keywords

Histological image segmentation splitting overlapping cells neuroblastoma 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Siamak Tafavogh
    • 1
  • Karla Felix Navarro
    • 1
  • Daniel R. Catchpoole
    • 1
  • Paul J. Kennedy
    • 1
  1. 1.Centre for Quantum Computation & Intelligent Systems, Faculty of Engineering and Information TechnologyUniversity of TechnologySydneyAustralia

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