Data-Parallel MRI Brain Segmentation in Clinicial Use
- Structural MRI brain analysis and segmentation is a crucial part in the daily routine in neurosurgery for intervention planning. Exemplarily, the free software FSL-FAST (FMRIB’s Segmentation Library – FMRIB’s Automated Segmentation Tool) in version 4 is used for segmentation of brain tissue types. To speed up the segmentation procedure by parallel execution, we transferred FSL-FAST to a GeneralStructural MRI brain analysis and segmentation is a crucial part in the daily routine in neurosurgery for intervention planning. Exemplarily, the free software FSL-FAST (FMRIB’s Segmentation Library – FMRIB’s Automated Segmentation Tool) in version 4 is used for segmentation of brain tissue types. To speed up the segmentation procedure by parallel execution, we transferred FSL-FAST to a General Purpose Graphics Processing Unit (GPGPU) using Open Computing Language (OpenCL) [1]. The necessary steps for parallelization resulted in substantially different and less useful results. Therefore, the underlying methods were revised and adapted yielding computational overhead. Nevertheless, we achieved a speed-up factor of 3.59 from CPU to GPGPU execution, as well providing similar useful or even better results.…
| Author: | Joachim Weber, Christian Doenitz, Alexander BrawanskiORCiDGND, Christoph PalmOTHORCiDGND |
|---|---|
| DOI: | https://doi.org/10.1007/978-3-662-46224-9_67 |
| Parent Title (German): | Bildverarbeitung für die Medizin 2015; Algorithmen - Systeme - Anwendungen; Proceedings des Workshops vom 15. bis 17. März 2015 in Lübeck |
| Subtitle (German): | Porting FSL-Fastv4 to GPGPUs |
| Publisher: | Springer |
| Place of publication: | Berlin |
| Document Type: | conference proceeding (article) |
| Language: | English |
| Year of first Publication: | 2015 |
| Release Date: | 2019/12/20 |
| Tag: | Brain Segmentation; General Purpose Graphic Processing Unit; Magnetic Resonance Imaging; Parallel Execution; Voxel Spacing |
| GND Keyword: | Kernspintomografie; Gehirn; Bildsegmentierung; Parallelverarbeitung |
| First Page: | 389 |
| Last Page: | 394 |
| Institutes: | Fakultät Informatik und Mathematik |
| Research Center of Biomedical Engineering - RCBE | |
| Fakultät Informatik und Mathematik / Labor Regensburg Medical Image Computing (ReMIC) | |
| Begutachtungsstatus: | peer-reviewed |
| research focus: | Gesundheit und Soziales |
| Licence (German): | |
| Frontdoor-URL: | https://opus4.kobv.de/opus4-oth-regensburg/116 |
