Bibliographic Details
| Title: |
3D Tortuosity computation as a shape descriptor and its application to brain structure analysis |
| Authors: |
Maria-Julieta Mateos, Ernesto Bribiesca, Adolfo Guzmán-Arenas, Wendy Aguilar, Jorge A. Marquez-Flores |
| Source: |
BMC Medical Imaging, Vol 24, Iss 1, Pp 1-12 (2024) |
| Publisher Information: |
BMC, 2024. |
| Publication Year: |
2024 |
| Collection: |
LCC:Medical technology |
| Subject Terms: |
3D tortuosity, Brain morphology, Alzheimer’s disease, Discrete tortuosity, Medical technology, R855-855.5 |
| More Details: |
Abstract In this study, we propose a novel method for quantifying tortuosity in 3D voxelized objects. As a shape characteristic, tortuosity has been widely recognized as a valuable feature in image analysis, particularly in the field of medical imaging. Our proposed method extends the two-dimensional approach of the Slope Chain Code (SCC) which creates a one-dimensional representation of curves. The utility of 3D tortuosity ( $$\tau _{3D}$$ τ 3 D ) as a shape descriptor was investigated by characterizing brain structures. The results of the $$\tau _{3D}$$ τ 3 D computation on the central sulcus and the main lobes revealed significant differences between Alzheimer’s disease (AD) patients and control subjects, suggesting its potential as a biomarker for AD. We found a $$p |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1471-2342 |
| Relation: |
https://doaj.org/toc/1471-2342 |
| DOI: |
10.1186/s12880-024-01312-6 |
| Access URL: |
https://doaj.org/article/1cd9936e4cb2453bba77158a8906155b |
| Accession Number: |
edsdoj.1cd9936e4cb2453bba77158a8906155b |
| Database: |
Directory of Open Access Journals |
