A Comparison of Generative Adversarial Networks for Automated Prostate Cancer Detection on T2-weighted MRI

A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.

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CROPro: A tool for automated cropping of prostate MR images

SCOPE-RL: A python library for offline reinforcement learning, off-policy evaluation, and selection

Python API for reading and manipulating polygon data of Electronic Navigational Charts (ENC)

A lightweight framework that enables the packaging of Python3.x code as co-simulation FMUs

Python version of the "A quality control system for automated prostate segmentation on T2-weighted MRI"

🌸 Notebooks for making publish-worthy visualizations using WHO breast cancer data

Python version of the AutoRef Normalization method for prostate T2W MRI images

Anomaly detection with diffusion models

Generative Models by Stability AI

Latex code for making neural networks diagrams

Using relativism to improve GAN-based Adversarial Attacks. 🦾

A framework for high-performance medical image processing, neural network inference and visualization

Code for reproducing f-AnoGAN training and anomaly scoring

Official implementation of Fixed-Point GAN - ICCV 2019

A quality control system for automated prostate segmentation on T2-weighted MRI

Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition