| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6035099 | NeuroImage | 2011 | 13 Pages |
Abstract
⺠Random forest for automatic segmentation of MS lesions in 3D MR images ⺠Features: multi-channel MR intensities, priors, long-range spatial context, symmetry ⺠Quantitative evaluation shows significant improvement over all earlier methods ⺠A ranking of the most discriminative features and channels is proposed ⺠The automatically learned decision sequence mimics the state-of-the-art pipeline
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Authors
Ezequiel Geremia, Olivier Clatz, Bjoern H. Menze, Ender Konukoglu, Antonio Criminisi, Nicholas Ayache,