Lifted Auto-Context Forests for Brain Tumour Segmentation

BrainLes@MICCAI, pp. 171-183, 2016.

Cited by: 16|Bibtex|Views30|Links
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Abstract:

We revisit Auto-Context Forests for brain tumour segmentation in multi-channel magnetic resonance images, where semantic context is progressively built and refined via successive layers of Decision Forests (DFs). Specifically, we make the following contributions: (1) improved generalization via an efficient node-splitting criterion based ...More

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