QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy-Reference-Cited by-同舟云学术

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QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy

Published:2019-02 Issue: Volume:186 Page:713-727
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Guha Roy Abhijit,Conjeti Sailesh,Navab Nassir,Wachinger Christian

Funder

Bavarian State Ministry of Education, Science and the Arts

Alzheimer's Disease Neuroimaging Initiative

National Institutes of Health

DOD ADNI

National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference51 articles.

1. Imaging structural co-variance between human brain regions;Alexander-Bloch;Nat. Rev. Neurosci.,2013

2. Unified segmentation;Ashburner;Neuroimage,2005

3. Formulating spatially varying performance in the statistical fusion framework;Asman;IEEE Trans. Med. Imag.,2012

4. A reproducible evaluation of ants similarity metric performance in brain image registration;Avants;Neuroimage,2011

5. Segnet: a Deep Convolutional Encoder-decoder Architecture for Image Segmentation;Badrinarayanan,2015

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