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Title: Active contours for overlapping cervical cell segmentation

Authors: Flávio H.D. Araújo; Romuere R.V. Silva; Fátima N.S. Medeiros; Jeová Farias Rocha Neto; Paulo Henrique Calaes Oliveira; Andrea G. Campos Bianchi; Daniela Ushizima

Addresses: Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil; Information Systems, Federal University of Piauí, Picos, Piauí, Brazil; Berkeley Institute for Data Science, University of California – Berkeley, Berkeley, California, USA; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA ' Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil; Information Systems, Federal University of Piauí, Picos, Piauí, Brazil; Berkeley Institute for Data Science, University of California – Berkeley, Berkeley, California, USA; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA ' Department of Teleinformatics Engineering, Federal University of Ceará, Fortaleza, Ceará, Brazil ' Brown University, Brown School of Engineering, Providence, Rhode Island, USA ' Computing Department, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil ' Computing Department, Federal University of Ouro Preto, Ouro Preto, Minas Gerais, Brazil ' Berkeley Institute for Data Science, University of California – Berkeley, Berkeley, California, USA; Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA

Abstract: The nuclei and cytoplasm segmentation of cervical cells is a well studied problem. However, the current segmentation algorithms are not robust to clinical practice due to the high computational cost or because they cannot accurately segment cells with high overlapping. In this paper, we propose a method that is capable of segmenting both cytoplasm and nucleus of each individual cell in a clump of overlapping cells. The proposed method consists of three steps: 1) cellular mass segmentation; 2) nucleus segmentation; 3) cytoplasm identification based on an active contour method. We carried out experiments on both synthetic and real cell images. The performance evaluation of the proposed method showed that it was less sensitive to the increase in the number of cells per image and the overlapping ratio against two other existing algorithms. It has also achieved a promising low processing time and, hence, it has the potential to support expert systems for cervical cell recognition.

Keywords: ABSnake; active contour; cervical cells; medical image; nuclei and cytoplasm segmentation; overlapping cells; pap test.

DOI: 10.1504/IJBET.2021.10035163

International Journal of Biomedical Engineering and Technology, 2021 Vol.35 No.1, pp.70 - 92

Received: 23 Aug 2017
Accepted: 12 Jan 2018

Published online: 25 Jan 2021 *

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