Ivan I. Maximov1, Farida Grinberg2, Irene Neuner1, 3, Nadim Jon Shah1, 4
1Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich GmbH, Juelich, Germany; 2Institute of Neuroscience and Medicine 4, Forschungszentrum Juelich, Juelich, Germany; 3Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany; 4Department of Neurology, RWTH Aachen University, Aachen, Germany
Clinical diffusion imaging frequently suffers from multiple artefacts. As a consequence, many corrupted datasets cannot be used in further analysis and/or medical treatments. We have developed a robust post-processing framework that allows one to recover the degraded datasets and to return them to use. In order to demonstrate the advantages of the developed framework, the results obtained by the robust approach with other post-processing algorithms are compared. We show the benefits of the robust post-processing framework using voxelwise analysis by TBSS software from FSL package.