Abstract
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 language | English |
|---|---|
| Title of host publication | Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries |
| Editors | Alessandro Crimi, Bjoern Menze, Oskar Maier, Mauricio Reyes, Heinz Handels |
| Number of pages | 11 |
| Volume | 9556 |
| Publisher | Springer International Publishing |
| Publication date | 05.10.2016 |
| Pages | 119 - 130 |
| ISBN (Print) | 978-3-319-30857-9 |
| ISBN (Electronic) | 978-3-319-30858-6 |
| DOIs | |
| Publication status | Published - 05.10.2016 |
| Event | Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, First International Workshop, Brainles 2015, Held in Conjuction with MICCAI 2015 - Munich, Germany Duration: 05.10.2015 → 09.10.2015 |
