Metadata-Version: 2.1
Name: antspyt1w
Version: 0.1.8
Summary: T1w human neuroimage processing with antspyx
Home-page: https://github.com/stnava/ANTsPyT1w
Author: Avants, Gosselin, Tustison
Author-email: stnava@gmail.com
License: Apache 2.0
Description: # ANTsPyT1w
        
        ## reference processing for t1-weighted neuroimages (human)
        
        the outputs of these processes can be used for data inspection/cleaning/triage
        as well for interrogating neuroscientific hypotheses.
        
        this package also keeps track of the latest preferred algorithm variations for
        production environments.
        
        install by calling (within the source directory):
        
        ```
        python setup.py install
        ```
        
        or install via `pip install antspyt1w`
        
        # what this will do
        
        - provide example data
        
        - brain extraction
        
        - denoising
        
        - n4 bias correction
        
        - brain parcellation into tissues, hemispheres, lobes and regions
        
        - hippocampus specific segmentation
        
        - t1 hypointensity segmentation and classification *exploratory*
        
        - deformable registration with robust and repeatable parameters
        
        - registration-based labeling of major white matter tracts
        
        - helpers that organize and annotate segmentation variables into data frames
        
        - hypothalamus segmentation *FIXME/TODO*
        
        
        the two most time-consuming processes are hippocampus-specific segentation
        (because it uses augmentation) and registration.  both take 10-20 minutes
        depending on your available computational resources and the data.  both
        could be made computationally cheaper at the cost of accuracy/reliability.
        
        # first time setup
        
        ```python
        import antspyt1w
        antspyt1w.get_data()
        ```
        
        NOTE: `get_data` has a `force_download` option to make sure the latest
        package data is installed.
        
        # example processing
        
        ```python
        import os
        os.environ["TF_NUM_INTEROP_THREADS"] = "8"
        os.environ["TF_NUM_INTRAOP_THREADS"] = "8"
        os.environ["ITK_GLOBAL_DEFAULT_NUMBER_OF_THREADS"] = "8"
        
        import antspyt1w
        import antspynet
        import ants
        
        ##### get example data + reference templates
        # NOTE:  PPMI-3803-20120814-MRI_T1-I340756 is a good example of our naming style
        # Study-SubjectID-Date-Modality-UniqueID
        # where Modality could also be measurement or something else
        fn = antspyt1w.get_data('PPMI-3803-20120814-MRI_T1-I340756', target_extension='.nii.gz' )
        img = ants.image_read( fn )
        
        # generalized default processing
        myresults = antspyt1w.hierarchical( img, output_prefix = '/tmp/XXX' )
        
        ##### organize summary data into data frames - user should pivot these to columns
        # and attach to unique IDs when accumulating for large-scale studies
        # see below for how to easily pivot into wide format
        # https://stackoverflow.com/questions/28337117/how-to-pivot-a-dataframe-in-pandas
        
        
        ```
        
        An example "full study" (at small scale) is illustrated in `~/.antspyt1w/run_dlbs.py`
        which demonstrates/comments on:
        - how to aggregate dataframes
        - how to pivot to wide format
        - how to join with a demographic/metadata file
        - visualizing basic outcomes.
        
        ## to publish a release
        
        ```
        python3 -m build
        python -m twine upload -u username -p password  dist/*
        ```
        
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