A novel solution based on scale invariant feature transform descriptors and deep learning for the detection of suspicious regions in mammogram images

A novel solution based on scale invariant feature transform descriptors and deep learning for the detection of suspicious regions in mammogram images

Background: Deep learning methods have become popular for their high-performance rate in the classification and detection of events in computer vision tasks. Transfer learning paradigm is widely adopted to apply pretrained convolutional neural network (CNN) on medical domains overcoming the problem...

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Bibliographic Details
Main Authors: Alessandro Bruno, Edoardo Ardizzone, Salvatore Vitabile, Massimo Midiri
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2020-01-01
Series:Journal of Medical Signals and Sensors
Subjects:
classification
computer-assisted image processing
computing methodologies
deep learning
digital mammography
Online Access:http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2020;volume=10;issue=3;spage=158;epage=173;aulast=Bruno

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http://www.jmssjournal.net/article.asp?issn=2228-7477;year=2020;volume=10;issue=3;spage=158;epage=173;aulast=Bruno

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