Article: Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images Journal: International Journal of Biomedical Engineering and Technology (IJBET) 2021 Vol.35 No.3 pp.223 - 241 Abstract: In this paper, we propose a complete automated framework for white blood cells differential count in peripheral blood and bone marrow images, in order to reduce the analysis time and increase the accuracy of several blood disorders diagnosis. A new colour transformation is first proposed to highlight the white blood cells regions. Then, a marker controlled watershed algorithm is used to segment the region of interest. The nucleus and cytoplasm are subsequently separated. In the identification step, a set of colour, texture and morphological features are extracted from both nucleus and cytoplasm regions. Next, the performances of a random forest classifier on a set of microscopic images are compared and evaluated. The obtained results reveal high recognition accuracies for both segmentation and classification stage. Inderscience Publishers - linking academia, business and industry through research

Title: Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images

Authors: Mohammed Lamine Benomar; Amine Chikh; Xavier Descombes; Mourtada Benazzouz

Addresses: Computer Science Department, Genie Biomedical Laboratory, Abou-Bekr Belkaid University, Tlemcen, Algeria ' Computer Science Department, Genie Biomedical Laboratory, Abou-Bekr Belkaid University, Tlemcen, Algeria ' French Institute for Research in Computer Science and Automation (INRIA), Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis (I3S), Côte d'Azur University, Nice, France ' Computer Science Department, Genie Biomedical Laboratory, Abou-Bekr Belkaid University, Tlemcen, Algeria

Abstract: In this paper, we propose a complete automated framework for white blood cells differential count in peripheral blood and bone marrow images, in order to reduce the analysis time and increase the accuracy of several blood disorders diagnosis. A new colour transformation is first proposed to highlight the white blood cells regions. Then, a marker controlled watershed algorithm is used to segment the region of interest. The nucleus and cytoplasm are subsequently separated. In the identification step, a set of colour, texture and morphological features are extracted from both nucleus and cytoplasm regions. Next, the performances of a random forest classifier on a set of microscopic images are compared and evaluated. The obtained results reveal high recognition accuracies for both segmentation and classification stage.

Keywords: white blood cells; WBCs; cells segmentation; cells classification; colour transformation; texture features; morphological features; peripheral blood images; bone marrow images.

DOI: 10.1504/IJBET.2021.113729

International Journal of Biomedical Engineering and Technology, 2021 Vol.35 No.3, pp.223 - 241

Received: 11 Sep 2017
Accepted: 26 Feb 2018
Published online: 22 Mar 2021 *

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Title: Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images

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