Details

Autor(en) / Beteiligte

• Frandsen, Jesper
• Hobolth, Asger
• Østergaard, Leif
• Vestergaard-Poulsen, Peter
• Vedel Jensen, Eva B

Titel

Bayesian regularization of diffusion tensor images

Ist Teil von

• Biostatistics (Oxford, England), 2007-10, Vol.8 (4), p.784-799

Ort / Verlag

England: Oxford University Press

Erscheinungsjahr

2007

Link zum Volltext

Quelle

Electronic Journals Library

Beschreibungen/Notizen

• Diffusion tensor imaging (DTI) is a powerful tool in the study of the course of nerve fiber bundles in the human brain. Using DTI, the local fiber orientation in each image voxel can be described by a diffusion tensor which is constructed from local measurements of diffusion coefficients along several directions. The measured diffusion coefficients and thereby the diffusion tensors are subject to noise, leading to possibly flawed representations of the 3-dimensional (3D) fiber bundles. In this paper, we develop a Bayesian procedure for regularizing the diffusion tensor field, fully utilizing the available 3D information of fiber orientation. The use of the procedure is exemplified on synthetic and in vivo data.