Abstract
In this paper we report a method to automatically segment the internal part of globus pallidus (GPi) on the pre-operative low-resolution magnetic resonance images (MRIs) of patients affected by Parkinson's disease. Herein we used an ultra-high resolution human brain dataset as electronic atlas of reference on which we segmented the GPi. First, we registered the ultra-high resolution dataset on the low-resolution dataset using a landmarks-based rigid registration. Then an affine and a non-rigid surface-based registration guided by the structures that surround the target was applied in order to propagate the labels of the GPi on the low-resolution un-segmented dataset and to accurately outline the target. The mapping of the atlas on the low-resolution MRI provided a highly accurate anatomical detail that can be useful for localizing the target.
| Original language | English (US) |
|---|---|
| Title of host publication | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 |
| Pages | 5706-5709 |
| Number of pages | 4 |
| DOIs | |
| State | Published - 2011 |
| Externally published | Yes |
| Event | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States Duration: Aug 30 2011 → Sep 3 2011 |
Publication series
| Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
|---|---|
| ISSN (Print) | 1557-170X |
Other
| Other | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 |
|---|---|
| Country/Territory | United States |
| City | Boston, MA |
| Period | 8/30/11 → 9/3/11 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics
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