Detection of breast cancer in mammography images using intelligent models
description: Amongst the several cancer types, incidence of breast cancer is the highest in women. Breast cancer can be diagnosed and treated effectively through various screening methods and computer-aided detection systems (CADs). However, conventional computer-aided diagnosis (CAD) programs for detecting potential cancers on mammograms are lacking diagnostic accuracy and require upgradation. The advances in machine learning, particularly with the use of deep (multi-layered) convolutional neural networks, have allowed artificial intelligence to create a transformation in CAD that has improved models' prediction quality. The outline of this chapter includes a structured method for predicting presenting breast cancer stages, identification, segmentation and classification of lesions, and breast density assessment using the current technological models which includes artificial intelligence, deep learning, and machine learning. 2024, IGI Global. All rights reserved.
creator: Sharma V.; Rawat Y.; Surve G.; Rai R.H.
source: Green AI-Powered Intelligent Systems for Disease Prognosis, pp. 241-260.
publisher: IGI Global
date: 2024-01-01
rights: Restricted Access
relation: ISBN: 979-836931244-5; 979-836931243-8
format: Online
language: English
type: Book chapter
coverage: Sharma V., Christ University, India; Rawat Y., Institute for Technology and Management, Mumbai, India; Surve G., Institute for Technology and Management, Mumbai, India; Rai R.H., Delhi Pharmaceutical Sciences and Research University, India