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2016 | OriginalPaper | Buchkapitel

Lifted Auto-Context Forests for Brain Tumour Segmentation

verfasst von : Loic Le Folgoc, Aditya V. Nori, Siddharth Ancha, Antonio Criminisi

Erschienen in: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

Verlag: Springer International Publishing

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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 on hold-out estimates, (2) increased compactness at a tree-level, thereby yielding shallow discriminative ensembles trained orders of magnitude faster, and (3) guided semantic bagging that exposes latent data-space semantics captured by forest pathways. The proposed framework is practical: the per-layer training is fast, modular and robust. It was a top performer in the MICCAI 2016 BRATS (Brain Tumour Segmentation) challenge, and this paper aims to discuss and provide details about the challenge entry.

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Vorheriges Kapitel Anatomy-Guided Brain Tumor Segmentation and Classification

Nächstes Kapitel Segmentation of Gliomas in Pre-operative and Post-operative Multimodal Magnetic Resonance Imaging Volumes Based on a Hybrid Generative-Discriminative Framework

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As an illustration on WT layers. The 4 (WT) clusters are obtained from (the single DF of) the first WT layer. The second and third WT layers each consist of 4 distinct (50-tree) DFs, each of which is trained on cluster-specific data. At test time, voxels \(\varvec{\mathrm {x}}\) pass through the first WT layer and are assigned a cluster \(k_{\varvec{\mathrm {x}}}\!\in \!\{1\cdots 4\}\). Then for the second and third layers, they are sent through the DF specific to the \(k_{\varvec{\mathrm {x}}}\)-th cluster. The same process is followed for TC and ET layers.

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Titel: Lifted Auto-Context Forests for Brain Tumour Segmentation
verfasst von: Loic Le Folgoc
Aditya V. Nori
Siddharth Ancha
Antonio Criminisi
Verlag: Springer International Publishing
Buch: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
Print ISBN: 978-3-319-55523-2

Electronic ISBN: 978-3-319-55524-9

Copyright-Jahr: 2016
DOI: https://doi.org/10.1007/978-3-319-55524-9_17

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