Title: Detection of abnormal blood cells by segmentation and classification

Authors: Abdellatif Bouzid-Daho; Mohamed Boughazi; Eric Petit

Addresses: Department of Electronic, Faculty of Engineering Science, Laboratoire d'Etude et de Recherche en Instrumentation et en Communication d'Annaba, University of Badji Mokhtar, Annaba, Algeria ' Department of Electronic, Faculty of Engineering Science, Laboratoire d'Etude et de Recherche en Instrumentation et en Communication d'Annaba, University of Badji Mokhtar, Annaba, Algeria ' Laboratoire Images, Signaux et Systèmes Intelligents (LiSSi), University Paris-Est Créteil, France

Abstract: Leukaemia is a cancer of the hematopoietic cells. The detection of abnormal blood cells before cancer degeneration is a medical problem. The aim of our work is to obtain maximum recognition rate of leukaemia. We propose the development of a system based on mathematical morphology and k-means methods capable of segmentation, classification, and detection of the cancerous blood cells. This allows the characterisation and the description the cancerous region, which is an important task in the interpretation and diagnosis of pathologies present in blood. The segmentation was carried out using an efficient and fast algorithmic processing. It turns out that the proposed system shows to better segmentation and classification for tested images. The obtained experimental results are very encouraging which help hematologists for identification of abnormal blood cells.

Keywords: leukaemia; k-means; segmentation; classification; diagnostic; abnormal blood cells.

DOI: 10.1504/IJMEI.2019.096892

International Journal of Medical Engineering and Informatics, 2019 Vol.11 No.1, pp.57 - 70

Received: 22 Dec 2016
Accepted: 05 Jul 2017
Published online: 13 Dec 2018 *

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