Lesion segmentation from multimodal MRI using random forest following ischemic stroke-Reference-Cited by-同舟云学术

Lesion segmentation from multimodal MRI using random forest following ischemic stroke

Published:2014-09 Issue: Volume:98 Page:324-335
ISSN:1053-8119
Container-title:NeuroImage
language:en
Short-container-title:NeuroImage

Author:

Mitra Jhimli,Bourgeat Pierrick,Fripp Jurgen,Ghose Soumya,Rose Stephen,Salvado Olivier,Connelly Alan,Campbell Bruce,Palmer Susan,Sharma Gagan,Christensen Soren,Carey Leeanne

Funder

Australian Research Council

Publisher

Elsevier BV

Subject

Cognitive Neuroscience,Neurology

Reference67 articles.

1. Fully automatic segmentation of white matter hyperintensities in MR images of the elderly;Admiraal-Behloul;NeuroImage,2005

2. Correlating lesion size and location to deficits after ischemic stroke: the influence of accounting for altered peri-necrotic tissue and incidental silent infarcts;Alexander;Behav. Brain Funct.,2010

3. Automatic segmentation of different-sized white matter lesions by voxel probability estimation;Anbeek;Med. Image Anal.,2004

4. Probabilistic segmentation of white matter lesions in MR imaging;Anbeek;NeuroImage,2004

5. Magnetic resonance imaging of acute stroke;Baird;J. Cereb. Blood Flow Metal.,1998

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