NDLI: Mammographic mass classification according to Bi-RADS lexicon

Content Provider	IET Digital Library
Author	Chokri, Ferkous Farida, Merouani Hayet
Abstract	The goal of this study is to propose a computer-aided diagnosis system to differentiate between four breast imaging reporting and data system (Bi-RADS) classes in digitised mammograms. This system is inspired by the approach of the doctor during the radiologic examination as it was agreed in BI-RADS, where masses are described by their form, their boundary and their density. The segmentation of masses in the authors’ approach is manual because it is supposed that the detection is already made. When the segmented region is available, the features extraction process can be carried out. 22 visual characteristics are automatically computed from shape, edge and textural properties; only one human feature is used in this study, which is the patient's age. Classification is finally done using a multi-layer perceptron according to two separate schemes; the first one consists of classify masses to distinguish between the four BI-RADS classes (2, 3, 4 and 5). In the second one the authors classify abnormalities on two classes (benign and malign). The proposed approach has been evaluated on 480 mammographic masses extracted from the digital database for screening mammography, and the obtained results are encouraging.
Starting Page	189
Ending Page	198
Page Count	10
ISSN	17519632
Volume Number	11
e-ISSN	17519640
Issue Number	Issue 3, Apr (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/11/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2016.0244
Journal	IET Computer Vision
Publisher Date	2016-10-27
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Bi-RADS Lexicon Biology And Medical Computing Biomedical Imaging/measurement Breast Cancer Breast Imaging Reporting And Data System Cancer Computer Vision And Image Processing Technique Digitised Mammograms Feature Extraction Image Classification Image Recognition Mammographic Mass Classification Mammography Medical Image Processing Multilayer Perceptron Multilayer Perceptrons Neural Computing Technique Patient Age Patient Diagnostic Method And Instrumentation Radiography And Computed Tomography X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	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
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