Segmenting neuroblastoma tumor images and splitting overlapping cells using shortest paths between cell contour convex regions

Publication Type:
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, 7885 LNAI pp. 171 - 175
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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. © 2013 Springer-Verlag.
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