Automated nucleus and cytoplasm segmentation of overlapping cervical cells

Lu, Zhi, Carneiro, Gustov and Bradley, Andrew P. (2013). Automated nucleus and cytoplasm segmentation of overlapping cervical cells. In: Kensaku Mori, Ichiro Sakuma, Yoshinobu Sato, Christian Barillot and Nassir Navab, Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings. 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, Nagoya-shi, Japan, (452-460). 22 - 26 September 2013. doi:10.1007/978-3-642-40811-3_57


Author Lu, Zhi
Carneiro, Gustov
Bradley, Andrew P.
Title of paper Automated nucleus and cytoplasm segmentation of overlapping cervical cells
Conference name 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013
Conference location Nagoya-shi, Japan
Conference dates 22 - 26 September 2013
Proceedings title Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013 - 16th International Conference, Proceedings   Check publisher's open access policy
Journal name Lecture Notes in Computer Science   Check publisher's open access policy
Place of Publication Heidelberg, Germany
Publisher Springer
Publication Year 2013
Year available 2013
Sub-type Fully published paper
DOI 10.1007/978-3-642-40811-3_57
Open Access Status
ISBN 9783642408106
9783642408113
9783642407628
9783642407635
9783642407598
ISSN 0302-9743
1611-3349
Editor Kensaku Mori
Ichiro Sakuma
Yoshinobu Sato
Christian Barillot
Nassir Navab
Volume 8149
Issue PART 1
Start page 452
End page 460
Total pages 9
Collection year 2014
Language eng
Abstract/Summary 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.
Subjects 1700 Computer Science
2614 Theoretical Computer Science
Keyword Overlapping cell segmentation
Pap smear image analysis
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ

 
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