Awesome GAN for Medical Imaging

A curated list of awesome GAN resources in medical imaging, inspired by the other awesome-* initiatives.

For a complete list of GANs in general computer vision, please visit really-awesome-gan.

To complement or correct it, please contact me at xiy525@mail.usask.ca or send a pull request.

Overview

Low Dose CT Denoising

  • Generative Adversarial Networks for Noise Reduction in Low-Dose CT [TMI]
  • Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss [arXiv]
  • Sharpness-aware Low dose CT denoising using conditional generative adversarial network [JDI] [code]

Segmentation

  • SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation [arXiv]
  • Adversarial training and dilated convolutions for brain MRI segmentation [arXiv]
  • Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks [arXiv]
  • Automatic Liver Segmentation Using an Adversarial Image-to-Image Network [arXiv]
  • Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images [MICCAI17]
  • SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays [arXiv]
  • Adversarial Deep Structured Nets for Mass Segmentation from Mammograms [arXiv] [code]
  • Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth [arXiv]

Detection

  • Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery [arXiv]
  • Generative adversarial networks for brain lesion detection [JMI]
  • Adversarial Networks for the Detection of Aggressive Prostate Cancer [arXiv]
  • Visual Feature Attribution using Wasserstein GANs [arXiv]

Medical Image Synthesis

  • Medical Image Synthesis with Context-Aware Generative Adversarial Networks [arXiv]
  • Deep MR to CT Synthesis using Unpaired Data [arXiv]
  • Synthesizing Filamentary Structured Images with GANs [arXiv] [code]
  • Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks (GANs) [arXiv]
  • Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks [arXiv]
  • Synthetic Medical Images from Dual Generative Adversarial Networks [arXiv]
  • Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results [arXiv]
  • Towards Adversarial Retinal Image Synthesis [arXiv]
  • End-to-end Adversarial Retinal Image Synthesis [TMI] (published vision of the above preprint)
  • Adversarial Image Synthesis for Unpaired Multi-Modal Cardiac Data [SASHIMI 2017]
  • Biomedical Data Augmentation Using Generative Adversarial Neural Networks [ICANN 2017]
  • Towards Virtual H&E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks [ICCV2017 workshop]
  • How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis [arXiv]
  • Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training [arXiv]
  • Unsupervised Histopathology Image Synthesis [arXiv]
  • Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks [arXiv]

Reconstruction

  • Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks [arXiv]
  • Deep Generative Adversarial Networks for Compressed Sensing (GANCS) Automates MRI [arXiv] [code]
  • Accelerated Magnetic Resonance Imaging by Adversarial Neural Network [DLMIA MICCAI 2017]
  • Deep De-Aliasing for Fast Compressive Sensing MRI [arXiv]

Classification

  • Semi-supervised Assessment of Incomplete LV Coverage in Cardiac MRI Using Generative Adversarial Nets [SASHIMI 2017]
  • Generalization of Deep Neural Networks for Chest Pathology Classification in X-Rays Using Generative Adversarial Networks [arXiv]
  • Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks [arXiv] [code]
  • Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification [arXiv]