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Abstract
Diffusion MRI is a complex technique, where new discoveries and implementations occur at a fast pace. The expertise needed for data analyses and accurate and reproducible results is increasingly demanding and requires multidisciplinary collaborations. In the present work we introduce Reproducible Tract Profiles 2 (RTP2), a set of flexible and automated methods to analyze anatomical MRI and diffusion weighted imaging (DWI) data for reproducible tractography. RTP2 reads structural MRI data and processes them through a succession of serialized containerized analyses. We describe the DWI algorithms used to identify white-matter tracts and their summary metrics, the flexible architecture of the platform, and the tools to programmatically access and control the computations. The combination of these three components provides an easy-to-use automatized tool developed and tested over 20 years, to obtain usable and reliable state-of-the-art diffusion metrics at the individual and group levels for basic research and clinical practice.
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1 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); BCBL, Basque Center on Cognition, Brain and Language, Donostia-San Sebastián, Spain (GRID:grid.423986.2) (ISNI:0000 0004 0536 1366); Stanford University, Wu Tsai Neurosciences Institute, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); IKERBASQUE, Basque Foundation for Science, Bilbao, Spain (GRID:grid.424810.b) (ISNI:0000 0004 0467 2314)
2 BCBL, Basque Center on Cognition, Brain and Language, Donostia-San Sebastián, Spain (GRID:grid.423986.2) (ISNI:0000 0004 0536 1366)
3 BCBL, Basque Center on Cognition, Brain and Language, Donostia-San Sebastián, Spain (GRID:grid.423986.2) (ISNI:0000 0004 0536 1366); IKERBASQUE, Basque Foundation for Science, Bilbao, Spain (GRID:grid.424810.b) (ISNI:0000 0004 0467 2314)
4 Stanford University, Department of Psychology, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956); Stanford University, Wu Tsai Neurosciences Institute, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)