artur112 Goto Github PK

3d-mri-brain-features-classification-using-autoencoder-regularization

PyTorch arrangement of a brain features classification using VAE as regularization. Inspired by the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654) and Suyog Jadhav's work.

3dscaffoldimaging

brain_tumour_segmentation

Code for training a 3DUnet for Brain tumour segmentation from Brats 2019 dataset; for feature extraction from the segmented volumes and for survival prediction. Run train.py for training, segment.py for segmenting test scans and evaluate.py for evaluating the performance of those segmentations. Basic code also written to perform survival prediction with a random forest classifiier.

hospital_monitoring

patterncw2

plug

Plug is a browser extension for users of the Internet Computer that allows you to access your ICP, Cycles, and other tokens as well as log into IC apps with one click.