Automated acute lymphoblastic leukaemia detection system using microscopic images

被引：8

作者：

Sukhia, Komal Nain ^{[1
]}

Ghafoor, Abdul ^{[1
]}

Riaz, Muhammad Mohsin ^{[2
]}

Iltaf, Naima ^{[1
]}

机构：

[1] NUST, Islamabad, Pakistan

[2] COMSATS Islamabad, CAST, Islamabad, Pakistan

来源：

IET IMAGE PROCESSING | 2019年 / 13卷 / 13期

关键词：

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; automated acute lymphoblastic leukaemia detection system; sparse representation; CLASSIFICATION;

D O I：

10.1049/iet-ipr.2018.5471

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：2548 / 2553

页数：6

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