A novel stacked sparse denoising autoencoder for mammography restoration to visual interpretation of breast lesion

This paper proposes a deep unsupervised learning based denoising autoencoder model for the restoration of degraded mammogram with visual interpretation of breast lumps or lesion in mammography images (called SSDAE). The proposed model attempts to intensify the underexposed and abnormal structural re...

Full description

Saved in:

Bibliographic Details
Published in:	Evolutionary intelligence Vol. 14; no. 1; pp. 133 - 149
Main Authors:	Ghosh, Swarup Kr, Biswas, Biswajit, Ghosh, Anupam
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2021 Springer Nature B.V
Subjects:	Algorithms Applications of Mathematics Artificial Intelligence Bioinformatics Control Engineering Feature extraction Image reconstruction Image restoration Mathematical and Computational Engineering Mechatronics Noise reduction Robotics Special Issue Statistical Physics and Dynamical Systems Target recognition Deep learning KL divergence Mammogram restoration Sparse autoencoder Convolutional autoencoder
ISSN:	1864-5909, 1864-5917
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!