Alessandro Daducci
Signal Processing Lab (LTS5), EPFL, Switzerland
Emmanuel Caruyer
Department of Radiology, University of Pennsylvania, USA
Maxime Descoteaux
Sherbrooke Connectivity Imaging Lab (SCIL), Universit´e de Sherbrooke, Canada
Jean-Philippe Thiran
Signal Processing Lab (LTS5), EPFL, Switzerland
University Hospital Center (CHUV) and University of Lausanne (UNIL), Switzerland
Website
http://hardi.epfl.ch/static/events/2013_ISBI/
Challenge Abstract
Validation is the bottleneck for the diffusion magnetic resonance imaging (MRI) community. Diffusion MRI is a powerful MRI modality which is sensitive to the random movement of the water molecules in biological tissues. By studying the anisotropy of this diffusion process in white matter it is possible to highlight structures otherwise invisible with other imaging modalities and to infer the neuronal wiring of the brain. The study of this connectivity is of major importance in a clinical perspective, with particular emphasis on neurological disorders which, nowadays, affect up to one billion people worldwide.
The state-of-the-art Diffusion Spectrum Imaging (DSI) [1] modality is known to provide good imaging quality but is too time-consuming to be of real interest for practical applications. Accelerated acquisitions, relying on a smaller number of sampling points, are thus required. In the last few years a multitude of new reconstruction approaches have been proposed to recover the local intra-voxel fiber structure. Some of them aim at improving the quality of the reconstructions while others focus on reducing the acquisition time. However, when a new algorithm is proposed, the performances are normally assessed with ad-hoc synthetic data and evaluation criteria. Hence, when proposing a new algorithm, it can be really difficult to compare the performances against the state-of-theart techniques. This aspect is even more crucial in a clinical perspective, as the availability of a comprehensive comparison of available reconstruction methods, highlighting strengths and weaknesses of each approach, might help clinicians in the choice of the most adequate diffusion MRI technique for a specific clinical application.
The diffusion MRI reconstruction challenge is organized with the aim to provide all researchers in this field with a common framework to assess the performances of their own algorithms and fairly compare their results against other approaches. The purpose of the contest is to compare different reconstruction schemes on the same synthetic data and under controlled conditions. The competitors will be asked to provide the best estimation of the configuration of fiber compartments of a common dataset by using their proposed algorithms.
Dr. Wong is the Founding Chair for Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, where he holds the John S. Dunn, Sr. Distinguished Endowed Chair in Biomedical Engineering. He is also a Professor of Radiology, Pathology, Laboratory Medicine, Neurology, and Neurosciences at Cornell University; the Director of Translational Research at Methodist Cancer Center; Vice Chair of Radiology, Chief of Medical Physics, and Chief Research Information Officer at The Methodist Hospital at Texas Medical Center.
John Sedat is Professor Emeritus in Biochemistry and Biophysics at the University of California, San Francisco. He received his Ph.D. in Biology from Caltech in Pasadena, CA in 1970 followed by postdoctoral study under Fred Sanger at the MRC in Cambridge, England. Subsequently, he spent approximately a year at the Hebrew University at Hadassah in Jerusalem, Israel where the Drosophila and chromosome study started. Several years at Yale followed, and he has been at UCSF since 1977.
