| Literature DB >> 29899682 |
Shan Cong1, Maher Rizkalla2, Paul Salama2, Shannon L Risacher3, John D West3, Yu-Chien Wu3, Liana Apostolova3, Eileen Tallman3, Andrew J Saykin3, Li Shen3.
Abstract
The hippocampus is widely studied in neuroimaging field as it plays important roles in memory and learning. However, the critical subfield information is often not explored in most hippocampal studies. We previously proposed a method for hippocampal subfield morphometry by integrating FreeSurfer, FSL, and SPHARM tools. But this method had some limitations, including the analysis of T1-weighted MRI scans without detailed subfield information and hippocampal registration without using important subfield information. To bridge these gaps, in this work, we propose a new framework for building a surface atlas of hippocampal subfields from high resolution T2-weighted MRI scans by integrating state-of-the-art methods for automated segmentation of hippocampal subfields and landmark-free, subfield-aware registration of hippocampal surfaces. Our experimental results have shown the promise of the new framework.Entities:
Year: 2017 PMID: 29899682 PMCID: PMC5995468 DOI: 10.1109/MWSCAS.2016.7870109
Source DB: PubMed Journal: Conf Proc (Midwest Symp Circuits Syst) ISSN: 1548-3746