Automated acute lymphoblastic leukaemia detection system using microscopic images. Issue 13 (11th October 2019)

• Record Type: Journal Article
• Authors: Sukhia, Komal Nain; Ghafoor, Abdul; Riaz, Muhammad Mohsin; Iltaf, Naima
• Is Part Of: IET image processing. Volume 13:Issue 13(2019)
• Page Start: 2548
• Page End: 2553
• Publication Date: 2019-10-11
• Subjects: cellular biophysics -- principal component analysis -- expectation‐maximisation algorithm -- feature extraction -- medical image processing -- image segmentation -- image classification -- blood -- cancer; microscopic images -- automatic approach -- acute lymphoblastic leukaemia classification -- white blood cell nuclei -- expectation maximisation algorithm -- feature extraction -- principal component analysis -- automated acute lymphoblastic leukaemia detection system -- sparse representation; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.5471
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : An automatic and novel approach for acute lymphoblastic leukaemia classification is proposed. The proposed scheme is based on pre‐processing and segmentation of white blood cell nuclei using expectation maximisation algorithm, feature extraction, feature selection using principal component analysis and classification using sparse representation. The accuracy of the proposed scheme significantly outperforms the existing schemes in terms of acute lymphoblastic leukaemia classification.