Shape analysis of the human association pathways
Shape analysis has been widely used in digital image processing and computer vision, but they have not been utilized to compare the structural characteristics of the human association pathways. Here we used shape analysis to derive length, area, volume, and shape metrics from diffusion MRI tractogra...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2020-12-01
|
| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811920308156 |
| _version_ | 1818844713098149888 |
|---|---|
| author | Fang-Cheng Yeh |
| author_facet | Fang-Cheng Yeh |
| author_sort | Fang-Cheng Yeh |
| collection | DOAJ |
| description | Shape analysis has been widely used in digital image processing and computer vision, but they have not been utilized to compare the structural characteristics of the human association pathways. Here we used shape analysis to derive length, area, volume, and shape metrics from diffusion MRI tractography and utilized them to study the morphology of human association pathways. The reliability analysis showed that shape descriptors achieved moderate to good test-retest reliability. Further analysis on association pathways showed left dominance in the arcuate fasciculus, cingulum, uncinate fasciculus, frontal aslant tract, and right dominance in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The superior longitudinal fasciculus has a mixed lateralization profile with different metrics showing either left or right dominance. The analysis of between-subject variations shows that the overall layout of the association pathways does not variate a lot across subjects, as shown by low between-subject variation in length, span, diameter, and radius. In contrast, the area of the pathway innervation region has a considerable between-subject variation. A follow-up analysis is warranted to thoroughly investigate the nature of population variations and their structure-function correlation. |
| first_indexed | 2024-12-19T05:18:08Z |
| format | Article |
| id | doaj.art-ab0d3fcfadf2450eac28f7ab7d6321d2 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-19T05:18:08Z |
| publishDate | 2020-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-ab0d3fcfadf2450eac28f7ab7d6321d22022-12-21T20:34:35ZengElsevierNeuroImage1095-95722020-12-01223117329Shape analysis of the human association pathwaysFang-Cheng Yeh0Department of Neurological Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United StatesShape analysis has been widely used in digital image processing and computer vision, but they have not been utilized to compare the structural characteristics of the human association pathways. Here we used shape analysis to derive length, area, volume, and shape metrics from diffusion MRI tractography and utilized them to study the morphology of human association pathways. The reliability analysis showed that shape descriptors achieved moderate to good test-retest reliability. Further analysis on association pathways showed left dominance in the arcuate fasciculus, cingulum, uncinate fasciculus, frontal aslant tract, and right dominance in the inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The superior longitudinal fasciculus has a mixed lateralization profile with different metrics showing either left or right dominance. The analysis of between-subject variations shows that the overall layout of the association pathways does not variate a lot across subjects, as shown by low between-subject variation in length, span, diameter, and radius. In contrast, the area of the pathway innervation region has a considerable between-subject variation. A follow-up analysis is warranted to thoroughly investigate the nature of population variations and their structure-function correlation.http://www.sciencedirect.com/science/article/pii/S1053811920308156Diffusion MRITractographyAutomatic fiber trackingShape analysisShape descriptor |
| spellingShingle | Fang-Cheng Yeh Shape analysis of the human association pathways NeuroImage Diffusion MRI Tractography Automatic fiber tracking Shape analysis Shape descriptor |
| title | Shape analysis of the human association pathways |
| title_full | Shape analysis of the human association pathways |
| title_fullStr | Shape analysis of the human association pathways |
| title_full_unstemmed | Shape analysis of the human association pathways |
| title_short | Shape analysis of the human association pathways |
| title_sort | shape analysis of the human association pathways |
| topic | Diffusion MRI Tractography Automatic fiber tracking Shape analysis Shape descriptor |
| url | http://www.sciencedirect.com/science/article/pii/S1053811920308156 |
| work_keys_str_mv | AT fangchengyeh shapeanalysisofthehumanassociationpathways |