| nipreps/fmriprep |
581 |
|
0 |
1 |
about 2 years ago |
178 |
November 22, 2023 |
278 |
apache-2.0 |
HTML |
| fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results. |
| nipreps/smriprep |
111 |
|
1 |
4 |
over 2 years ago |
64 |
December 08, 2023 |
55 |
apache-2.0 |
Python |
| Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools) |
| sappelhoff/pyprep |
106 |
|
0 |
1 |
over 2 years ago |
11 |
October 27, 2023 |
19 |
mit |
Python |
| A Python implementation of the Preprocessing Pipeline (PREP) for EEG data |
| automaticanalysis/automaticanalysis |
70 |
|
0 |
0 |
over 2 years ago |
0 |
|
39 |
mit |
MATLAB |
| Automatic Analysis (aa) |
| HALFpipe/HALFpipe |
56 |
|
0 |
0 |
about 2 years ago |
0 |
|
96 |
other |
Python |
| ENIGMA HALFpipe is a user-friendly software that facilitates reproducible analysis of fMRI data |
| akeshavan/mindcontrol |
48 |
|
0 |
0 |
almost 7 years ago |
0 |
|
22 |
other |
JavaScript |
| MindControl is an app for quality control of neuroimaging pipeline outputs. Demo: |
| miykael/fmriflows |
42 |
|
0 |
0 |
almost 4 years ago |
0 |
|
2 |
bsd-3-clause |
MATLAB |
| fmriflows is a consortium of many (dependent) fMRI analysis pipelines, including anatomical and functional pre-processing, univariate 1st and 2nd-level analysis, as well as multivariate pattern analysis. |
| kschan0214/sepia |
41 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
MATLAB |
| Matlab GUI pipeline application for quantitative susceptibility mapping (QSM) |
| AaltoImagingLanguage/conpy |
33 |
|
0 |
0 |
over 2 years ago |
0 |
|
5 |
bsd-3-clause |
Python |
| Python package for power mapping and functional connectivity using DICS |
| APPIAN-PET/APPIAN |
32 |
|
0 |
0 |
about 3 years ago |
0 |
|
13 |
mit |
JavaScript |
| APPIAN is an open-source automated software pipeline for analyzing PET images in conjunction with MRI. The goal of APPIAN is to make PET tracer kinetic data analysis easy for users with moderate computing skills and to facilitate reproducible research. |
