Journal article
Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI
IEEE transactions on medical imaging, Vol.33(99), pp.384-399
02/01/2014
DOI: 10.1109/TMI.2013.2285500
PMID: 24132007
Abstract
Validation is arguably the bottleneck in the diffusion 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.
Details
- Title: Subtitle
- Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI
- Creators
- Alessandro Daducci - Laboratoire de Traitement du signal [EPFL] / Signal Processing LaboratoriesErick Jorge Canales-Rodríguez - Fundació per a la Investigació i la Docència Maria Angustias Giménez [Barcelone]Maxime Descoteaux - Sherbrooke Connectivity Imaging Lab [Sherbrooke]Eleftherios Garyfallidis - Sherbrooke Connectivity Imaging Lab [Sherbrooke]Yaniv Gur - Scientific Computing and Imaging InstituteYing Chia Lin - Department of Computer ScienceMerry Mani - Department of Electrical Engineering [Rochester]Sylvain L Merlet - Computational Imaging of the Central Nervous SystemMichael Paquette - SCILAlonso Ramirez-Manzanares - Centro de Investigación en MatemáticasMarco Reisert - Department of Radiology, Medical PhysicsPaulo Reis Rodrigues - Department of Personality, Assessment and Psychological Treatments [Barcelona]Farshid Sepehrband - Centre for Advanced Imaging [Brisbane]Emmanuel Caruyer - Computational Imaging of the Central Nervous SystemJeiran Choupan - Centre for Advanced Imaging [Brisbane]Rachid Deriche - Computational Imaging of the Central Nervous SystemMathews Jacob - Department of Electrical Engineering [Rochester]Gloria Menegaz - Department of Computer ScienceVesna Prckovska - Clinical and experimental neuroimmunology [IDIBAPS]Mariano Rivera - Centro de Investigación en MatemáticasYves Wiaux - Laboratoire de Traitement du signal [EPFL] / Signal Processing LaboratoriesJean-Philippe Thiran - Laboratoire de Traitement du signal [EPFL] / Signal Processing Laboratories
- Resource Type
- Journal article
- Publication Details
- IEEE transactions on medical imaging, Vol.33(99), pp.384-399
- DOI
- 10.1109/TMI.2013.2285500
- PMID
- 24132007
- NLM abbreviation
- IEEE Trans Med Imaging
- ISSN
- 0278-0062
- eISSN
- 1558-254X
- Publisher
- Institute of Electrical and Electronics Engineers
- Language
- English
- Date published
- 02/01/2014
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Iowa Neuroscience Institute; Radiation Oncology
- Record Identifier
- 9984051783002771
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