Image Features for Brain Lesion Segmentation Using Random Forests

Oskar Maier, Matthias Wilms, Heinz Handels


From clinical practice as well as research methods arises the need for accurate, reproducible and reliable segmentation of pathological areas from brain MR scans. This paper describes a set of hand-selected, voxel-based image features highly suitable for the tissue discrimination task. Embedded in a random decision forest framework, the proposed method was applied to sub-acute ischemic stroke (ISLES 2015 - SISS), acute ischemic stroke (ISLES 2015 - SPES) and glioma (BRATS 2015) segmentation with only minor adaptation. For all of these three challenges, our generic approach received high ranks, among them a second place. The outcome underlines the robustness of our features for segmentation in brain MR, while simultaneously stressing the necessity for highly specialized solution to achieve state-of-the-art performance.
Original languageEnglish
Title of host publicationBrainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries
EditorsAlessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels
Number of pages11
PublisherSpringer International Publishing
Publication date05.10.2016
Pages119 - 130
ISBN (Print)978-3-319-30857-9
ISBN (Electronic)978-3-319-30858-6
Publication statusPublished - 05.10.2016
EventBrainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, First International Workshop, Brainles 2015, Held in Conjuction with MICCAI 2015
- Munich, Germany
Duration: 05.10.201509.10.2015


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