2021 IEEE International Conference on Image Processing
19-22 September 2021 • Anchorage, Alaska, USA
Imaging Without Borders
| Paper ID | BIO-1.11 | ||
| Paper Title | CONNECTIVITY BASED FUNCTIONAL SEGMENTATION OF THE BRAINSTEM | ||
| Authors | Nandinee Fariah Haq, Christina Zhang, Linlin Gao, Tianze Yu, Martin J. McKeown, University of British Columbia, Canada | ||
| Session | BIO-1: Biomedical Signal Processing 1 | ||
| Location | Area C | ||
| Session Time: | Monday, 20 September, 13:30 - 15:00 | ||
| Presentation Time: | Monday, 20 September, 13:30 - 15:00 | ||
| Presentation | Poster | ||
| Topic | Biomedical Signal Processing: Medical image analysis | ||
| IEEE Xplore Open Preview | Click here to view in IEEE Xplore | ||
| Abstract | The human brainstem is an anatomically complex and compact structure, and many neurologic diseases are frequently associated with brainstem dysfunction. Despite its importance in brain functioning and neurodegenerative processes, the brainstem and its functional sub-structures are relatively unexplored in medical image analysis. Here we present a data-driven framework to extract functional sub-regions from the brainstem. We first apply a novel motion correction scheme to the brainstem. A simple network is then derived by examining the correlation of BOLD signals between brainstem voxels, and a network community quality function is optimized to extract the sub-networks within the brainstem. We applied this technique to fMRI data from fifteen healthy participants and found 84 group-level, spatially contiguous sub-regions within the brainstem. Association of these regions with other cortical and subcortical brain regions were investigated to assist in interpreting what underlying anatomical structures were associated with the subregions. Although the proposed method was originally developed for the brainstem, the proposed framework has the potential to be integrated into studies investigating functional sub-regions from other cortical or subcortical brain regions. | ||