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Detection of Breast Cancer in Mammography Images Using Intelligent Models
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Author(s): Vandana Sharma (Christ University, India), Yogita Rawat (Institute for Technology and Management, Mumbai, India), Gauri Surve (Institute for Technology and Management, Mumbai, India)and Richa Hirendra Rai (Delhi Pharmaceutical Sciences and Research University, India)
Copyright: 2024
Pages: 20
Source title:
Green AI-Powered Intelligent Systems for Disease Prognosis
Source Author(s)/Editor(s): Ashish Khanna (Maharaja Agrasen Institute of Technology, India)and Saikat Gochhait (Symbiosis Institute of Digital and Telecom Management, Symbiosis International (Deemed), India & Samara State Medical University, Russia)
DOI: 10.4018/979-8-3693-1243-8.ch013
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Abstract
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.
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