This Python project, developed as a coding challenge for the Center of Intelligence Fellowship at UCSF, focuses on image processing for neuroscience research using the ChestMNIST dataset. The project aims to enhance image clarity and extract valuable information for ML research in neuroscience.
Utilizes NumPy and Matplotlib libraries to load and explore the ChestMNIST dataset. Prints the available files in the dataset for transparency.
Displays the sixth image from the test_images file in grayscale. Implements a pixel inversion technique for enhanced contrast and visual appeal.
Applies a Gaussian filter to the original image to reduce pixelation and smooth edges. Displays the filtered image to demonstrate improvements.
Replicates the image processing steps for additional images (first and fourth images). Showcases the versatility of the code in handling various images.