Published 2013
| Version v1
Book section
4th Order Symmetric Tensors and Positive ADC Modelling
Creators
Contributors
Others:
- Computational Imaging of the Central Nervous System (ATHENA) ; Centre Inria d'Université Côte d'Azur (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Anna Vilanova and Carl-Fredrik Westin and Bernhard Burgeth
Description
High Order Cartesian Tensors (HOTs) were introduced in Generalized DTI (GDTI) to overcome the limitations of DTI. HOTs can model the apparent diffusion coefficient (ADC) with greater accuracy than DTI in regions with fiber heterogeneity. Although GDTI HOTs were designed to model positive diffusion, the straightforward least square (LS) estimation of HOTs doesn't guarantee positivity. In this chapter we address the problem of estimating 4th order tensors with positive diffusion profiles. Two known methods exist that broach this problem, namely a Riemannian approach based on the algebra of 4th order tensors, and a polynomial approach based on Hilbert's theorem on non-negative ternary quartics. In this chapter, we review the technicalities of these two approaches, compare them theoretically to show their pros and cons, and compare them against the Euclidean LS estimation on synthetic, phantom and real data to motivate the relevance of the positive diffusion profile constraint.
Abstract
International audienceAdditional details
Identifiers
- URL
- https://inria.hal.science/hal-00848513
- URN
- urn:oai:HAL:hal-00848513v1
Origin repository
- Origin repository
- UNICA