Detection of abnormal blood cells by segmentation and classification
by Abdellatif Bouzid-Daho; Mohamed Boughazi; Eric Petit
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 11, No. 1, 2019

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.

Online publication date: Thu, 13-Dec-2018

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