Semisupervised learning using denoising autoencoders for brain lesion detection and segmentation

The work explores the use of denoising autoencoders (DAEs) for brain lesion detection, segmentation, and false-positive reduction. Stacked denoising autoencoders (SDAEs) were pretrained using a large number of unlabeled patient volumes and fine-tuned with patches drawn from a limited number of patie...

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Bibliographic Details

Published in:	Journal of medical imaging (Bellingham, Wash.) Vol. 4; no. 4; p. 041311
Main Authors:	Alex, Varghese, Vaidhya, Kiran, Thirunavukkarasu, Subramaniam, Kesavadas, Chandrasekharan, Krishnamurthi, Ganapathy
Format:	Journal Article
Language:	English
Published:	United States 01.10.2017
Subjects:	deep learning stacked denoising autoencoder magnetic resonance imaging denoising autoencoder gliomas brain lesion
ISSN:	2329-4302
Online Access:	Get more information
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