Fuimaging
Framework to analyze Neuroimaging data
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Slicer | 1,339 | 4 months ago | 578 | other | C++ | |||||
| Multi-platform, free open source software for visualization and image computing. | ||||||||||
| Slicergitsvnarchive | 883 | 4 years ago | 25 | other | C++ | |||||
| Multi-platform, free open source software for visualization and image computing. | ||||||||||
| Dipy | 647 | 4 months ago | 155 | other | Python | |||||
| DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging. | ||||||||||
| Livianet | 133 | 4 years ago | 6 | mit | Python | |||||
| This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study" | ||||||||||
| Extensionsindex | 52 | 4 months ago | 25 | Python | ||||||
| Slicer extensions index | ||||||||||
| Brainextractor | 20 | a year ago | 2 | February 08, 2022 | 1 | mit | Python | |||
| A re-implementation of FSL's Brain Extraction Tool in Python | ||||||||||
| Brainmage | 20 | 2 years ago | 4 | other | Python | |||||
| Brain extraction in presence of abnormalities, using single and multiple MRI modalities | ||||||||||
| Trained Models | 19 | 6 months ago | 19 | Python | ||||||
| Trained TensorFlow models for 3D image processing | ||||||||||
| Deepbet | 16 | 5 months ago | mit | Python | ||||||
| Fast brain extraction using neural networks | ||||||||||
| Fmri_roi_analysis_tool | 10 | 5 months ago | 33 | November 09, 2023 | apache-2.0 | Python | ||||
| An analysis tool that uses per-voxel statistical maps in conjunction with FSL atlases to create per-region statistical maps. Current usage includes the creation of regional maps of temporal signal to noise ratio. | ||||||||||
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