Detection of abnormal blood cells by segmentation and classification

Autor:	Eric Petit, Mohamed Boughazi, Abdellatif Bouzid-Daho
Rok vydání:	2019
Předmět:	Computer science business.industry k-means clustering Biomedical Engineering Cancer Medicine (miscellaneous) Pattern recognition Health Informatics Mathematical morphology medicine.disease Biomaterials Haematopoiesis medicine Segmentation Abnormal blood cells Artificial intelligence business
Zdroj:	International Journal of Medical Engineering and Informatics. 11:57
ISSN:	1755-0661 1755-0653
DOI:	10.1504/ijmei.2019.096892
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92378573cca23c3916203189c2547ccb https://doi.org/10.1504/ijmei.2019.096892 Zobrazit plný text záznamu