（转）Awesome GAN for Medical Imaging

Awesome GAN for Medical Imaging

2018-08-10 09:32:43

 

This blog is copied from: https://github.com/xinario/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
• Segmentation
• Detection
• Medical Image Synthesis
• Reconstruction
• Classification
• Others

Low Dose CT Denoising

• [Generative Adversarial Networks for Noise Reduction in Low-Dose CT] [scholar] [TMI]
• [Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss] [scholar] [arXiv]
• [Sharpness-aware Low dose CT denoising using conditional generative adversarial network] [scholar] [arXiv] [JDI] [code]
• [Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography] [scholar] [arXiv]
• [Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising] [scholar] [arXiv]

Segmentation

• [SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation] [scholar] [arXiv]
• [Adversarial training and dilated convolutions for brain MRI segmentation] [scholar] [arXiv]
• [Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks] [scholar] [arXiv]
• [Automatic Liver Segmentation Using an Adversarial Image-to-Image Network] [scholar] [arXiv]
• [Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images] [scholar] [MICCAI17]
• [SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-rays] [scholar] [arXiv]
• [Adversarial Deep Structured Nets for Mass Segmentation from Mammograms] [scholar] [arXiv] [code]
• [Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth] [scholar] [arXiv]
• [Adversarial neural networks for basal membrane segmentation of microinvasive cervix carcinoma in histopathology images] [scholar] [ICMLC]
• [Unsupervised domain adaptation in brain lesion segmentation with adversarial networks] [scholar] [IPMI2017]
• [whole heart and great vessel segmentation with context aware generative adversarial network] [scholar] [BM]
• [Generative Adversarial Neural Networks for Pigmented and Non-Pigmented Skin Lesions Detection in Clinical Images] [scholar] [CSCS2017]
• [Generative Adversarial Networks to Segment Skin Lesions] [scholar] [ISBI2018]
• [A conditional adversarial network for semantic segmentation of brain tumor] [scholar] [arXiv]
• [Brain Tumor Segmentation Using an Adversarial Network] [scholar] [MICCAI Brainlesion workshop]
• [Joint Optic Disc and Cup Segmentation using Fully Convolutional and Adversarial Networks] [scholar] [OMIA2017]
• [Splenomegaly Segmentation using Global Convolutional Kernels and Conditional Generative Adversarial Networks] [scholar] [SPIE MI]

Detection

• [Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery] [scholar] [arXiv]
• [Generative adversarial networks for brain lesion detection] [scholar] [JMI]
• [Adversarial Networks for the Detection of Aggressive Prostate Cancer] [scholar] [arXiv]
• [Visual Feature Attribution using Wasserstein GANs] [scholar] [arXiv]
• [Unsupervised Detection of Lesions in Brain MRI using constrained adversarial auto-encoders] [scholar] [arXiv]

Medical Image Synthesis

• [Medical Image Synthesis with Context-Aware Generative Adversarial Networks] [scholar] [arXiv]
• [Medical Image Synthesis with Deep Convolutional Adversarial Networks] [scholar] [TBME] (published vision of the above preprint)
• [Deep MR to CT Synthesis using Unpaired Data] [scholar] [arXiv]
• [Synthesizing Filamentary Structured Images with GANs] [scholar] [arXiv] [code]
• [Synthesizing retinal and neuronal images with generative adversarial nets] [scholar] [MIA] (published vision of the above preprint)
• [Synthesis of Positron Emission Tomography (PET) Images via Multi-channel Generative Adversarial Networks] [scholar](GANs) [arXiv]
• [Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks] [scholar] [arXiv]
• [Synthetic Medical Images from Dual Generative Adversarial Networks] [scholar] [arXiv]
• [Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results] [scholar] [arXiv]
• [Towards Adversarial Retinal Image Synthesis] [scholar] [arXiv]
• [End-to-end Adversarial Retinal Image Synthesis] [scholar] [TMI] (published vision of the above preprint)
• [Adversarial Image Synthesis for Unpaired Multi-Modal Cardiac Data] [scholar] [SASHIMI 2017]
• [Biomedical Data Augmentation Using Generative Adversarial Neural Networks] [scholar] [ICANN 2017]
• [Towards Virtual H&E Staining of Hyperspectral Lung Histology Images Using Conditional Generative Adversarial Networks] [scholar] [ICCV2017 workshop]
• [How to Fool Radiologists with Generative Adversarial Networks? A Visual Turing Test for Lung Cancer Diagnosis] [scholar][arXiv]
• [Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training] [scholar] [arXiv]
• [Unsupervised Histopathology Image Synthesis] [scholar] [arXiv]
• [Image Synthesis in Multi-Contrast MRI with Conditional Generative Adversarial Networks] [scholar] [arXiv]
• [Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network] [scholar] [arXiv]
• [MRI Image-to-Image Translation for Cross-Modality Image Registration and Segmentation] [scholar] [arXiv]
• [Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size] [scholar] [arXiv]
• [Cross-Modality Synthesis from CT to PET using FCN and GAN Networks for Improved Automated Lesion Detection] [scholar] [arXiv]
• [MelanoGANs: High Resolution Skin Lesion Synthesis with GANs] [scholar] [arXiv]
• [Domain-adversarial neural networks to address the appearance variability of histopathology images] [scholar] [arXiv]
• [Neural Stain-Style Transfer Learning using GAN for Histopathological Images] [scholar] [arXiv]
• [Generative Adversarial Training for MRA Image Synthesis Using Multi-Contrast MRI ] [scholar] [arXiv]
• [Histopathology Stain-Color Normalization Using Generative Neural Networks] [scholar] [MIDL2018]
• [3D cGAN based cross-modality MR image synthesis for brain tumor segmentation] [scholar] [ISBI2018]
• [Deep CT to MR Synthesis using Paired and Unpaired Data] [scholar] [arXiv]
• [GAN-based synthetic brain MR image generation] [scholar] [ISBI2018]
• [StainGAN: Stain Style Transfer for Digital Histological Images] [scholar] [arXiv]
• [Adversarial Stain Transfer for Histopathology Image Analysis] [scholar] [TMI]
• [Chest x-ray generation and data augmentation for cardiovascular abnormality classification] [scholar] [SPIE MI2018]
• [blood vessel geometry synthesis using generative adversarial networks] [scholar] [MIDL2018]
• [Synergistic Reconstruction and Synthesis via Generative Adversarial Networks for Accelerated Multi-Contrast MRI] [scholar] [arXiv]
• [Stain normalization of histopathology images using generative adversarial networks] [scholar] [ISBI2018]
• [MedGAN: Medical Image Translation using GANs] [scholar] [arXiv]
• [Retinal Image Synthesis for CAD Development] [scholar] [ICIAR]
• [High-Resolution Mammogram Synthesis using Progressive Generative Adversarial Networks] [scholar] [arXiv]
• [High-resolution medical image synthesis using progressively grown generative adversarial networks] [scholar] [arXiv]
• [Learning Myelin Content in Multiple Sclerosis from Multimodal MRI through Adversarial Training] [scholar] [MICCAI2018]
• [Generation of structural MR images from amyloid PET: Application to MR-less quantification] [scholar] [JNM]
• [Task Driven Generative Modeling for Unsupervised Domain Adaptation Application to X-ray Image Segmentation] [scholar] [arXiv]

Reconstruction

• [Compressed Sensing MRI Reconstruction with Cyclic Loss in Generative Adversarial Networks] [scholar] [arXiv]
• [Compressed Sensing MRI Reconstruction using a Generative Adversarial Network with a Cyclic Loss] [scholar] [TMI](published version of the above preprint)
• [Deep Generative Adversarial Networks for Compressed Sensing (GANCS) Automates MRI] [scholar] [arXiv] [code]
• [Accelerated Magnetic Resonance Imaging by Adversarial Neural Network] [scholar] [DLMIA MICCAI 2017]
• [Deep De-Aliasing for Fast Compressive Sensing MR] [scholar] [arXiv]
• [3D conditional generative adversarial networks for high-quality PET image estimation at low dose] [scholar] [NI]

Classification

• [Semi-supervised Assessment of Incomplete LV Coverage in Cardiac MRI Using Generative Adversarial Nets] [scholar][SASHIMI 2017]
• [Generalization of Deep Neural Networks for Chest Pathology Classification in X-Rays Using Generative Adversarial Networks] [scholar] [arXiv]
• [Unsupervised Learning for Cell-level Visual Representation in Histopathology Images with Generative Adversarial Networks] [scholar] [arXiv] [code]
• [Synthetic Data Augmentation using GAN for Improved Liver Lesion Classification] [scholar] [arXiv]
• [GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification] [scholar][arXiv](extended version of above preprint)
• [Unsupervised and semi-supervised learning with Categorical Generative Adversarial Networks assisted by Wasserstein distance for dermoscopy image Classification] [scholar] [arXiv]
• [Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation] [scholar] [ISBI2018]

Others

• [Intraoperative Organ Motion Models with an Ensemble of Conditional Generative Adversarial Networks] [scholar] [arXiv]
• [Retinal Vasculature Segmentation Using Local Saliency Maps and Generative Adversarial Networks For Image Super Resolution] [scholar] [arXiv]
• [Adversarial training with cycle consistency for unsupervised super-resolution in endomicroscopy ] [scholar] [MIDL2018]
• [Brain MRI super-resolution using 3D generative adversarial networks ] [scholar] [MIDL2018]
• [Generative Spatiotemporal Modeling Of Neutrophil Behavior] [scholar] [ISBI2018]
• [Deformable medical image registration using generative adversarial networks] [scholar] [ISBI2018]
• [Adversarial Image Registration with Application for MR and TRUS Image Fusion] [scholar] [arXiv]
• [Exploiting the potential of unlabeled endoscopic video data with self-supervised learning] [scholar] [IJCARS]
• [Generative Adversarial Networks for MR-CT Deformable Image Registration] [scholar] [arXiv]