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PyDesigner v1.0: A Pythonic Implementation of the DESIGNER Pipeline for Diffusion Magnetic Resonance Imaging.
Dhiman, Siddhartha; Hickey, Reyna E; Thorn, Kathryn E; Moss, Hunter G; McKinnon, Emilie T; Adisetiyo, Vitria; Ades-Aron, Benjamin; Jensen, Jens H; Benitez, Andreana.
Afiliação
  • Dhiman S; Department of Neuroscience, Medical University of South Carolina.
  • Hickey RE; Department of Neurology, Medical University of South Carolina.
  • Thorn KE; Department of Neurology, Medical University of South Carolina.
  • Moss HG; Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina.
  • McKinnon ET; Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina.
  • Adisetiyo V; Department of Neuroscience, Medical University of South Carolina.
  • Ades-Aron B; Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine.
  • Jensen JH; Department of Neuroscience, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina; Department of Radiology and Radiological Science, Medical University of South Carolina; jense@musc.edu.
  • Benitez A; Department of Neurology, Medical University of South Carolina; Center for Biomedical Imaging, Medical University of South Carolina; benitez@musc.edu.
J Vis Exp ; (207)2024 May 17.
Article em En | MEDLINE | ID: mdl-38829110
ABSTRACT
PyDesigner is a Python-based software package based on the original Diffusion parameter EStImation with Gibbs and NoisE Removal (DESIGNER) pipeline (Dv1) for dMRI preprocessing and tensor estimation. This software is openly provided for non-commercial research and may not be used for clinical care. PyDesigner combines tools from FSL and MRtrix3 to perform denoising, Gibbs ringing correction, eddy current motion correction, brain masking, image smoothing, and Rician bias correction to optimize the estimation of multiple diffusion measures. It can be used across platforms on Windows, Mac, and Linux to accurately derive commonly used metrics from DKI, DTI, WMTI, FBI, and FBWM datasets as well as tractography ODFs and .fib files. It is also file-format agnostic, accepting inputs in the form of .nii, .nii.gz, .mif, and dicom format. User-friendly and easy to install, this software also outputs quality control metrics illustrating signal-to-noise ratio graphs, outlier voxels, and head motion to evaluate data integrity. Additionally, this dMRI processing pipeline supports multiple echo-time dataset processing and features pipeline customization, allowing the user to specify which processes are employed and which outputs are produced to meet a variety of user needs.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Imagem de Difusão por Ressonância Magnética Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Imagem de Difusão por Ressonância Magnética Limite: Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article