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

共 50 条

[31] Detection of Acute Leukaemia Cells Using Variety of Features and Neural Networks
Nasir, A. S. Abdul
Mashor, M. Y.
Rosline, H.
5TH KUALA LUMPUR INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING 2011 (BIOMED 2011), 2011, 35 : 40 - +
[32] Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system
Liu, Yaling
Xie, Hai
Zhao, Xinyu
Tang, Jiannan
Yu, Zhen
Wu, Zhenquan
Tian, Ruyin
Chen, Yi
Chen, Miaohong
Ntentakis, Dimitrios P.
Du, Yueshanyi
Chen, Tingyi
Hu, Yarou
Zhang, Sifan
Lei, Baiying
Zhang, Guoming
EPMA JOURNAL, 2024, 15 (01) : 39 - 51
[33] Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy images
Charfi, Said
El Ansari, Mohamed
Balasingham, Ilangko
IET IMAGE PROCESSING, 2019, 13 (06) : 1023 - 1030
[34] BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images
Atteia, Ghada
Alhussan, Amel A.
Samee, Nagwan Abdel
SENSORS, 2022, 22 (15)
[35] Automated detection of glaucoma using optical coherence tomography angiogram images
Chan, Yam Meng
Ng, E. Y. K.
Jahmunah, V.
Koh, Joel En Wei
Lih, Oh Shu
Leon, Leonard Yip Wei
Acharya, U. Rajendra
COMPUTERS IN BIOLOGY AND MEDICINE, 2019, 115
[36] Readiness for hospital discharge in primary caregivers for children with acute lymphoblastic leukaemia
Lu, Feng
Zhang, Ge
Zhao, Xiufang
Luo, Biru
JOURNAL OF CLINICAL NURSING, 2022, 31 (21-22) : 3213 - 3221
[37] Flow cytometry thresholds of myeloperoxidase detection to discriminate between acute lymphoblastic or myeloblastic leukaemia
Guy, Julien
Antony-Debre, Ileana
Benayoun, Emmanuel
Arnoux, Isabelle
Fossat, Chantal
Le Garff-Tavernier, Magali
Raimbault, Anna
Imbert, Michele
Maynadie, Marc
Lacombe, Francis
Bene, Marie C.
Wagner-Ballon, Orianne
BRITISH JOURNAL OF HAEMATOLOGY, 2013, 161 (04) : 551 - 555
[38] A Cascaded Classification-Segmentation Reversible System for Computer-Aided Detection and Cells Counting in Microscopic Peripheral Blood Smear Basophils and Eosinophils Images
Ashour, Amira S.
Wahba, Maram A.
Ghannam, Rami
IEEE ACCESS, 2021, 9 : 78883 - 78901
[39] An Enhanced Residual Architecture for Automated Detection of Bone Metastasis on Whole-Body SPECT Images
Li, Jianwei
Hao, Yusheng
Lin, Qiang
Cao, Yongchun
Man, Zhengxing
Wang, Weilan
IEEE ACCESS, 2025, 13 : 56100 - 56111
[40] Automated Detection and Classification of Liver Cancer from CT Images using HOG-SVM model
Al Sadeque, Zarif
Khan, Tanvirul Islam
Hossain, Quazi Delwar
Turaba, Mahbuba Yesmin
2019 5TH INTERNATIONAL CONFERENCE ON ADVANCES IN ELECTRICAL ENGINEERING (ICAEE), 2019, : 21 - 26

← 1 2 3 4 5 →