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* first proposition * As snippet * Add contributing * Change arch * Put contributing.md back in place + try fix links * Try linking outside docs * Test hooks * Remove hooks * 2e test hooks * Test more with hook * Test hooks on startup * Remove hooks * Test link with html * Test with html * Test fix broken links from Third Party * Test fix link third party * Test fix link third party2 * Apply to all links * Test link on Home * Add home folder * Test contributing.md kinking * Test snippet for contributing * Add symlink * Fix symlink * Remove .md from nav * Changes upon suggestions * Last fix * Fix lasts links
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../../CONTRIBUTING.md |
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- `adni-to-bids` - [ADNI: Alzheimer’s Disease Neuroimaging Initiative](../Converters/ADNI2BIDS.md) | ||
- `aibl-to-bids` - [AIBL: Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing](../Converters/AIBL2BIDS.md) | ||
- `genfi-to-bids` - [GENFI:Genetic Frontotemporal dementia Initiative](../Converters/GENFItoBIDS.md) | ||
- `habs-to-bids` - [HABS: Harvard Aging Brain Study](../Converters/HABS2BIDS.md) | ||
- `ixi-to-bids` - [IXI: Information eXtraction from Images](../Converters/IXItoBIDS.md) | ||
- `nifd-to-bids` - [NIFD: Neuroimaging in Frontotemporal Dementia](../Converters/NIFD2BIDS.md) | ||
- `oasis-to-bids` - [OASIS: Open Access Series of Imaging Studies](../Converters/OASIS2BIDS.md) | ||
- `oasis3-to-bids` - [OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer’s Disease](../Converters/OASIS3TOBIDS.md) | ||
- `ukb-to-bids` - [UK Biobank: Large-scale biomedical database and research resource in the United Kingdom](../Converters/UKBtoBIDS.md) | ||
- `adni-to-bids` - [ADNI: Alzheimer’s Disease Neuroimaging Initiative](./../Converters/ADNI2BIDS.md) | ||
- `aibl-to-bids` - [AIBL: Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing](./../Converters/AIBL2BIDS.md) | ||
- `genfi-to-bids` - [GENFI:Genetic Frontotemporal dementia Initiative](./../Converters/GENFItoBIDS.md) | ||
- `habs-to-bids` - [HABS: Harvard Aging Brain Study](./../Converters/HABS2BIDS.md) | ||
- `ixi-to-bids` - [IXI: Information eXtraction from Images](./../Converters/IXItoBIDS.md) | ||
- `nifd-to-bids` - [NIFD: Neuroimaging in Frontotemporal Dementia](./../Converters/NIFD2BIDS.md) | ||
- `oasis-to-bids` - [OASIS: Open Access Series of Imaging Studies](./../Converters/OASIS2BIDS.md) | ||
- `oasis3-to-bids` - [OASIS-3: Longitudinal Neuroimaging, Clinical, and Cognitive Dataset for Normal Aging and Alzheimer’s Disease](./../Converters/OASIS3TOBIDS.md) | ||
- `ukb-to-bids` - [UK Biobank: Large-scale biomedical database and research resource in the United Kingdom](./../Converters/UKBtoBIDS.md) |
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- Anatomical MRI | ||
- `t1-linear` - [Linear processing of T1w MR images](../Pipelines/T1_Linear.md): affine registration to the MNI standard space of T1 images | ||
- `flair-linear` - [Linear processing of FLAIR images](../Pipelines/FLAIR_Linear.md): affine registration to the MNI standard space of FLAIR images | ||
- `t1-volume` - [Processing of T1w MR images using SPM](../Pipelines/T1_Volume.md): tissue segmentation and spatial normalization | ||
- `t1-freesurfer` - [Processing of T1w MR images using FreeSurfer](../Pipelines/T1_FreeSurfer.md): cortical surface, subcortical structures and volumetrics | ||
- `t1-freesurfer-longitudinal` - [Longitudinal processing of T1w MR images using FreeSurfer](../Pipelines/T1_FreeSurfer_Longitudinal.md): cortical surface, subcortical structures and volumetrics | ||
- `t1-linear` - [Linear processing of T1w MR images](./../Pipelines/T1_Linear.md): affine registration to the MNI standard space of T1 images | ||
- `flair-linear` - [Linear processing of FLAIR images](./../Pipelines/FLAIR_Linear.md): affine registration to the MNI standard space of FLAIR images | ||
- `t1-volume` - [Processing of T1w MR images using SPM](./../Pipelines/T1_Volume.md): tissue segmentation and spatial normalization | ||
- `t1-freesurfer` - [Processing of T1w MR images using FreeSurfer](./../Pipelines/T1_FreeSurfer.md): cortical surface, subcortical structures and volumetrics | ||
- `t1-freesurfer-longitudinal` - [Longitudinal processing of T1w MR images using FreeSurfer](./../Pipelines/T1_FreeSurfer_Longitudinal.md): cortical surface, subcortical structures and volumetrics | ||
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- Diffusion MRI (DWI) | ||
- `dwi-preprocessing-*` - [DWI pre-processing](../Pipelines/DWI_Preprocessing.md): correction of head motion, magnetic susceptibility, eddy current and bias field induced distortions | ||
- `dwi-dti` - [DTI scalar maps (FA, MD, AD, RD) and spatial normalization](../Pipelines/DWI_DTI.md): extraction of DTI-based measures (FA, MD, AD, RD) | ||
- `dwi-connectome` - [Construction of structural connectome](../Pipelines/DWI_Connectome.md): computation of fiber orientation distributions, tractogram and connectome | ||
- `dwi-preprocessing-*` - [DWI pre-processing](./../Pipelines/DWI_Preprocessing.md): correction of head motion, magnetic susceptibility, eddy current and bias field induced distortions | ||
- `dwi-dti` - [DTI scalar maps (FA, MD, AD, RD) and spatial normalization](./../Pipelines/DWI_DTI.md): extraction of DTI-based measures (FA, MD, AD, RD) | ||
- `dwi-connectome` - [Construction of structural connectome](./../Pipelines/DWI_Connectome.md): computation of fiber orientation distributions, tractogram and connectome | ||
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- PET | ||
- [Introduction to concepts used in the PET pipelines](../Pipelines/PET_Introduction.md): partial volume correction and standardized uptake value ratio (SUVR) map computation | ||
- `pet-linear` - [Linear processing of PET images](../Pipelines/PET_Linear.md): affine registration to the MNI standard space and intensity normalization | ||
- `pet-volume` - [Volume-based processing of PET images](../Pipelines/PET_Volume.md): registration to T1w MRI, intensity normalization, partial volume correction and spatial normalization | ||
- `pet-surface` - [Surface-based processing of PET images](../Pipelines/PET_Surface.md): projection of the PET signal onto the subject’s cortical surface | ||
- `pet-surface-longitudinal` - [Surface-based longitudinal processing of PET images](../Pipelines/PET_Surface_Longitudinal.md): projection of the PET signal onto the subject’s cortical surface | ||
- [Introduction to concepts used in the PET pipelines](./../Pipelines/PET_Introduction.md): partial volume correction and standardized uptake value ratio (SUVR) map computation | ||
- `pet-linear` - [Linear processing of PET images](./../Pipelines/PET_Linear.md): affine registration to the MNI standard space and intensity normalization | ||
- `pet-volume` - [Volume-based processing of PET images](./../Pipelines/PET_Volume.md): registration to T1w MRI, intensity normalization, partial volume correction and spatial normalization | ||
- `pet-surface` - [Surface-based processing of PET images](./../Pipelines/PET_Surface.md): projection of the PET signal onto the subject’s cortical surface | ||
- `pet-surface-longitudinal` - [Surface-based longitudinal processing of PET images](./../Pipelines/PET_Surface_Longitudinal.md): projection of the PET signal onto the subject’s cortical surface | ||
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- Statistics | ||
- `statistics-surface` - [Surface-based mass-univariate analysis with SurfStat](../Pipelines/Stats_Surface.md) | ||
- `statistics-volume` - [Volume-based mass-univariate analysis with SPM](../Pipelines/Stats_Volume.md) | ||
- `statistics-surface` - [Surface-based mass-univariate analysis with SurfStat](./../Pipelines/Stats_Surface.md) | ||
- `statistics-volume` - [Volume-based mass-univariate analysis with SPM](./../Pipelines/Stats_Volume.md) | ||
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- Machine Learning | ||
- `machinelearning-prepare-spatial-svm` - [Prepare input data for spatially regularized SVM](../Pipelines/MachineLearning_PrepareSVM.md) | ||
- `machinelearning-classification` - [Classification based on machine learning](../Pipelines/MachineLearning_Classification.md) | ||
- `machinelearning-prepare-spatial-svm` - [Prepare input data for spatially regularized SVM](./../Pipelines/MachineLearning_PrepareSVM.md) | ||
- `machinelearning-classification` - [Classification based on machine learning](./../Pipelines/MachineLearning_Classification.md) | ||
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- Deep learning | ||
- You can use the [ClinicaDL framework](https://clinicadl.readthedocs.io/) for the reproducible processing of neuroimaging data with deep learning methods. |
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## Contact us ! | ||
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- Check for past answers on [Clinica Google Group](https://groups.google.com/forum/#!forum/clinica-user) | ||
- Start a [discussion](https://github.com/aramis-lab/clinica/discussions) on GitHub | ||
- Report an [issue](https://github.com/aramis-lab/clinica/issues) on Github |
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