Code snippets for preprocessing DTI/MRI neuroimaging data
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Updated
Mar 26, 2024 - Shell
Code snippets for preprocessing DTI/MRI neuroimaging data
Small plugins for some popular softwares to make neuroimaging analysis workflow easy
A volumetric version of the Mindboggle 101 atlas conveniently imported in FSL. This repo was used in Bedini, M., Olivetti, E., Avesani, P., & Baldauf, D. (2023). Accurate localization and coactivation profiles of the frontal eye field and inferior frontal junction: an ALE and MACM fMRI meta-analysis. Brain Structure and Function, 1-21.
A web application for documenting signs in Filipino Sign Language (FSL).
Automated quality control tools for diffusion MRI data
Normalising T1 weighted brain scans and lesions.
A simple script to deface (with use of fsl_deface) multiple T1/T2-weighetned files prepared according to the BIDS standard.
An automatic translation system from English text to Filipino Sign Language (FSL) using the E-Sign Approach
Preprocess head CT scans using python!
A repository for supplementary considerations required to run certain stroke segmentation algorithms
FSL integration using Python and Docker. Streamline neuroimaging workflows with ease.
Explore the neural basis of cognitive control with this repository's in-depth analysis of the Flanker Dataset using fMRI. Using bash scripting to streamline preprocessing and ROI analysis, while incorporating R scripts to explore brain region activity during the task.
An extensible fMRI Preprocessing Pipeline in nipype based on a 2015 Jonathan Power Pipeline
Pipelines for structural analysis for NeuroMet Project
Image analysis pipelines of qunatitative MRI (qMRI), including diffusion MRI (dMRI), in patients with adrenoleukodystrophy (ALD)
Docker image that provides a Ubuntu 16.04 (Xenial) with all CMP pre-requisite software installed
Nipype interface(s) wrapping the fsl_anat command line tool
The basic structural and diffusion MRI registration with pre-processing pipeline in Python.
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