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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Vydané v:	Journal of medical imaging (Bellingham, Wash.) Ročník 4; číslo 4; s. 041311
Hlavní autori:	Alex, Varghese, Vaidhya, Kiran, Thirunavukkarasu, Subramaniam, Kesavadas, Chandrasekharan, Krishnamurthi, Ganapathy
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 01.10.2017
Predmet:	deep learning stacked denoising autoencoder magnetic resonance imaging denoising autoencoder gliomas brain lesion
ISSN:	2329-4302
On-line prístup:	Zistit podrobnosti o prístupe
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