Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/83721
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Type: Conference paper
Title: Automated nucleus and cytoplasm segmentation of overlapping cervical cells
Author: Lu, Z.
Carneiro, G.
Bradley, A.
Citation: Proceedings of Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013 / K. Mori, I. Sakuma, Y. Sato, C. Barillot, N. Navab (eds.), pp.452-460
Publisher: Springer
Publisher Place: Germany
Issue Date: 2013
Series/Report no.: Lecture Notes in Computer Science
ISBN: 9783642407628
ISSN: 0302-9743
1611-3349
Conference Name: International Conference on Medical Image Computing and Computer-Assisted Intervention (16th : 2013 : Nagoya, Japan)
Statement of
Responsibility: 
Zhi Lu, Gustavo Carneiro, and Andrew P. Bradley
Abstract: In this paper we describe an algorithm for accurately segmenting the individual cytoplasm and nuclei from a clump of overlapping cervical cells. Current methods cannot undertake such a complete segmentation due to the challenges involved in delineating cells with severe overlap and poor contrast. Our approach initially performs a scene segmentation to highlight both free-lying cells, cell clumps and their nuclei. Then cell segmentation is performed using a joint level set optimization on all detected nuclei and cytoplasm pairs. This optimisation is constrained by the length and area of each cell, a prior on cell shape, the amount of cell overlap and the expected gray values within the overlapping regions. We present quantitative nuclei detection and cell segmentation results on a database of synthetically overlapped cell images constructed from real images of free-lying cervical cells. We also perform a qualitative assessment of complete fields of view containing multiple cells and cell clumps.
Keywords: Overlapping cell segmentation; Pap smear image analysis
Rights: © Springer-Verlag Berlin Heidelberg 2013
RMID: 0020132279
DOI: 10.1007/978-3-642-40811-3_57
Appears in Collections:Computer Science publications

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