Brain tumor segmentation from multimodal magnetic resonance images via sparse representation-Reference-Cited by-同舟云学术

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Brain tumor segmentation from multimodal magnetic resonance images via sparse representation

Published:2016-10 Issue: Volume:73 Page:1-13
ISSN:0933-3657
Container-title:Artificial Intelligence in Medicine
language:en
Short-container-title:Artificial Intelligence in Medicine

Author:

Li Yuhong,Jia Fucang,Qin Jing

Funder

Key Joint Program of National Natural Science Foundation and Guangdong Province of China

Shenzhen-Hong Kong Innovation Circle Funding Program

Guangdong Natural Science Foudation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Medicine (miscellaneous)

Reference47 articles.

1. Brain tumor segmentation from multispectral MRIs using sparse representation classification and Markov Random Field regularization;Warfield;IEEE Trans Med Imaging,2004

2. A survey of MRI based medical image analysis for brain tumor studies;Bauer;Phys Med Biol,2013

3. A novel content-based active model for brain tumor segmentation;Sachdeva;Magn Reson Imaging,2012

4. Fluid vector flow and application in brain tumor segmentation;Wang;IEEE Trans Biomed Eng,2009

5. Semi-automated brain tumor and edema segmentation using MRI;Xie;Eur J Radiol,2005

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