Robust Fusion of Diffusion MRI Data for Template Construction
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yang, Zhanlong | - |
dc.contributor.author | Chen, Geng | - |
dc.contributor.author | Shen, Dinggang | - |
dc.contributor.author | Yap, Pew-Thian | - |
dc.date.accessioned | 2021-09-03T00:11:21Z | - |
dc.date.available | 2021-09-03T00:11:21Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2017-10-11 | - |
dc.identifier.issn | 2045-2322 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/81918 | - |
dc.description.abstract | Construction of brain templates is generally carried out using a two-step procedure involving registering a population of images to a common space and then fusing the aligned images to form a template. In practice, image registration is not perfect and simple averaging of the images will blur structures and cause artifacts. In diffusion MRI, this is further complicated by intra-voxel inter-subject differences in fiber orientation, fiber configuration, anisotropy, and diffusivity. In this paper, we propose a method to improve the construction of diffusion MRI templates in light of inter-subject differences. Our method involves a novel q-space (i.e., wavevector space) patch matching mechanism that is incorporated in a mean shift algorithm to seek the most probable signal at each point in q-space. Our method relies on the fact that the mean shift algorithm is a mode seeking algorithm that converges to the mode of a distribution and is hence robust to outliers. Our method is therefore in effect seeking the most probable signal profile at each voxel given a distribution of signal profiles. Experimental results show that our method yields diffusion MRI templates with cleaner fiber orientations and less artifacts caused by intersubject differences in fiber orientation. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | NATURE PUBLISHING GROUP | - |
dc.subject | NONLOCAL MEANS | - |
dc.subject | IMAGE-ANALYSIS | - |
dc.subject | REGISTRATION | - |
dc.subject | REPRESENTATION | - |
dc.subject | MOMENTS | - |
dc.subject | ATLASES | - |
dc.title | Robust Fusion of Diffusion MRI Data for Template Construction | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Shen, Dinggang | - |
dc.identifier.doi | 10.1038/s41598-017-13247-w | - |
dc.identifier.scopusid | 2-s2.0-85031106286 | - |
dc.identifier.wosid | 000412781300018 | - |
dc.identifier.bibliographicCitation | SCIENTIFIC REPORTS, v.7 | - |
dc.relation.isPartOf | SCIENTIFIC REPORTS | - |
dc.citation.title | SCIENTIFIC REPORTS | - |
dc.citation.volume | 7 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | NONLOCAL MEANS | - |
dc.subject.keywordPlus | IMAGE-ANALYSIS | - |
dc.subject.keywordPlus | REGISTRATION | - |
dc.subject.keywordPlus | REPRESENTATION | - |
dc.subject.keywordPlus | MOMENTS | - |
dc.subject.keywordPlus | ATLASES | - |
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