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Gist 919bd3761b3b882347732f6d4b85bbad

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Aakeshavan
Last edited Feb 6, 2018
Created on Feb 6, 2018

This example demonstrates a pipeline for predicting brain data quality using deep learning models, applied to 2D slices extracted from a 3D neuroimaging file. It shows how a URL to a `.nii.gz` file is sent to an OpenFaaS serverless function, which generates and returns image slices that are then processed for display. The code uses Python libraries including Matplotlib, PIL, NumPy, and Requests, converting base64-encoded slices into grayscale images and visualizing them side by side. The visualization highlights the workflow of fetching remote brain imaging data and rendering its 2D projections for quality inspection.

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