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|Title:||Automated nucleus and cytoplasm segmentation of overlapping cervical cells|
|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|
|Series/Report no.:||Lecture Notes in Computer Science|
|Conference Name:||International Conference on Medical Image Computing and Computer-Assisted Intervention (16th : 2013 : Nagoya, Japan)|
|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|
|Appears in Collections:||Computer Science publications|
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