| Literature DB >> 24132007 |
Alessandro Daducci, Erick Jorge Canales-Rodríguez, Maxime Descoteaux, Eleftherios Garyfallidis, Yaniv Gur, Ying-Chia Lin, Merry Mani, Sylvain Merlet, Michael Paquette, Alonso Ramirez-Manzanares, Marco Reisert, Paulo Reis Rodrigues, Farshid Sepehrband, Emmanuel Caruyer, Jeiran Choupan, Rachid Deriche, Mathews Jacob, Gloria Menegaz, Vesna Prčkovska, Mariano Rivera, Yves Wiaux, Jean-Philippe Thiran.
Abstract
Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.Mesh:
Year: 2013 PMID: 24132007 DOI: 10.1109/TMI.2013.2285500
Source DB: PubMed Journal: IEEE Trans Med Imaging ISSN: 0278-0062 Impact factor: 10.048