Crossing Fibers Detection with an Analytical High Order Tensor Decomposition

Abstract : Diffusion magnetic resonance imaging (dMRI) is the only technique to probe in vivo and noninvasively the fiber structure of human brain white matter. Detecting the crossing of neuronal fibers remains an exciting challenge with an important impact in tractography. In this work, we tackle this challenging problem and propose an original and efficient technique to extract all crossing fibers from diffusion signals. To this end, we start by estimating, from the dMRI signal, the so-called Cartesian tensor fiber orientation distribution (CT-FOD) function, whose maxima correspond exactly to the orientations of the fibers. The fourth order symmetric positive definite tensor that represents the CT-FOD is then analytically decomposed via the application of a new theoretical approach and this decomposition is used to accurately extract all the fibers orientations. Our proposed high order tensor decomposition based approach is minimal and allows recovering the whole crossing fibers without any a priori information on the total number of fibers. Various experiments performed on noisy synthetic data, on phantom diffusion, data and on human brain data validate our approach and clearly demonstrate that it is efficient, robust to noise and performs favorably in terms of angular resolution and accuracy when compared to some classical and state-of-the-art approaches.
Type de document :
Article dans une revue
Computational and Mathematical Methods in Medicine, Hindawi Publishing Corporation, 2014, 2014, pp.1-18. 〈http://dx.doi.org/10.1155/2014/476837〉. 〈10.1155〉
Liste complète des métadonnées

https://hal.inria.fr/hal-01078352
Contributeur : Rachid Deriche <>
Soumis le : mardi 28 octobre 2014 - 17:05:50
Dernière modification le : jeudi 11 janvier 2018 - 16:16:51

Identifiants

  • HAL Id : hal-01078352, version 1
  • DOI : 10.1155

Collections

Citation

Thinhinane Megherbi, Mouloud Kachouane, Fatima Oulebsir Boumghar, Rachid Deriche. Crossing Fibers Detection with an Analytical High Order Tensor Decomposition. Computational and Mathematical Methods in Medicine, Hindawi Publishing Corporation, 2014, 2014, pp.1-18. 〈http://dx.doi.org/10.1155/2014/476837〉. 〈10.1155〉. 〈hal-01078352〉

Partager

Métriques

Consultations de la notice

110