Computer Vision News - December 2021

22 Introduction to Neuroscience Image Processing Setup !pip install numpy matplotlib !pip install nibabel !mkdir data !curl https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/27995283/sub01_sesanat- omy_T1w .nii.gz -o data/sub-01_ses-anatomy_T1w .nii.gz !curl https://s3-eu-west-1.amazonaws.com/pfigshare-u-files/27995286/sub01_sesper- ceptionNaturalImageTest01_taskperception_run01_bold .nii.gz -o data/sub-01_ses-per- ceptionNaturalImageTest01_task-perception_run-01_bold .nii.gz !ls data Introduction In the neuroscience community, MRI images are often saved, processed, and shared in NIfTI-1 format. The file extension is .nii (uncompressed) or .nii.gz (gzipped). A single NIfTI-1 file can contains either 3-D (spatial) or 4-D (spatial + temporal) MRI image. More information: https://nifti.nimh.nih.gov/nifti-1/ Visualization of NIfTI images • Use nibabel to handle NIfTI images: https://nipy.org/nibabel/ • nibabel.load load an NIfTI image as a nibabel image instance. • To obtain the image as a Numpy array, run np.asanyarray(<img>.dataobje) . Introduction to Neuroscience Image Processing using Jupyter Notebooks Hello again and welcome! Are you excited about neuroscience and coding with brains? This month it’s all about this. Let’s dive in. Without further ado, I am presenting you NIFTI, NIBABEL but also a short introduction (to be continued in the next issue) of General Linear Models (GLMs). We’ll startwith the requiredsetup, introductionandpresentation of data and how to use a Python Jupyter notebook to access and process them. There’s also an amazing package introduced here, it’s called BData from Kamitani lab (where amazing info were taken from) and here’s used as a machine learning data format which you can utilize in your later models. Enjoy and feel free to let me know if you use it in your project and how!