Your browser doesn't support javascript.
loading
Reproducible Tract Profiles 2 (RTP2) suite, from diffusion MRI acquisition to clinical practice and research.
Lerma-Usabiaga, Garikoitz; Liu, Mengxing; Paz-Alonso, Pedro M; Wandell, Brian A.
Afiliación
  • Lerma-Usabiaga G; Department of Psychology, Stanford University, 450 Serra Mall, Jordan Hall Building, Stanford, CA, 94305, USA. garikoitz@gmail.com.
  • Liu M; BCBL, Basque Center on Cognition, Brain and Language, Mikeletegi Pasealekua 69, 20009, Donostia-San Sebastián, Gipuzkoa, Spain. garikoitz@gmail.com.
  • Paz-Alonso PM; Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, 94305, USA. garikoitz@gmail.com.
  • Wandell BA; IKERBASQUE, Basque Foundation for Science, 48013, Bilbao, Spain. garikoitz@gmail.com.
Sci Rep ; 13(1): 6010, 2023 04 12.
Article en En | MEDLINE | ID: mdl-37045891
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Sustancia Blanca Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Encéfalo / Sustancia Blanca Idioma: En Revista: Sci Rep Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido