NDLI: Efficient computer-aided diagnosis technique for leukaemia cancer detection

Content Provider	IET Digital Library
Author	Abdulla, Alan Anwer
Abstract	Computer-aided diagnosis (CAD) is a common tool for the detection of diseases, particularly different types of cancers, based on medical images. Digital image processing thus plays a significant role in the processing and analysis of medical images for diseases identification and detection purposes. In this study, an efficient CAD system for the acute lymphoblastic leukaemia (ALL) detection is proposed. The proposed approach entails two phases. In the first phase, the white blood cells (WBCs) are segmented from the microscopic blood image. The second phase involves extracting important features, such as shape and texture features from the segmented cells. Eventually, on the extracted features, Naïve Bayes and k-nearest neighbour classifier techniques are implemented to identify the segmented cells into normal and abnormal cells. The performance of the proposed approach has been assessed through comprehensive experiments carried out on the well-known ALL-IDB data set of microscopic blood images. The experimental results demonstrate the superior performance of the proposed approach over the state-of-the-art in terms of accuracy rate in which achieved 98.7%.
Starting Page	4435
Ending Page	4440
Page Count	6
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 17, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0978
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/17
Journal	IET Image Processing
Publisher Date	2020-12-04
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Abnormal Cell Acute Lymphoblastic Leukaemia Detection Biology And Medical Computing Biomedical Imaging/measurement Biomedical Optical Imaging Blood CAD CAD System Cancer Cellular Biophysics Computer Vision And Image Processing Technique Computer-aided Diagnosis Technique Detection Purposes Digital Image Processing Diseases Diseases Identification Feature Extraction Image Classification Image Recognition Image Segmentation Image Texture K-nearest Neighbour Classifier Technique Leukaemia Cancer Detection Medical Image Medical Image Processing Microscopic Blood Image Optical And Laser Radiation Patient Diagnostic Method And Instrumentation Segmented Cell Texture Feature White Blood Cell
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
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