Medical Image Generation

26 papers with code • 5 benchmarks • 4 datasets

Medical image generation is the task of synthesising new medical images.

( Image credit: Towards Adversarial Retinal Image Synthesis )

Correction of out-of-focus microscopic images by deep learning

jiangdat/COMI Computational and Structural Biotechnology Journal 2022

Results To solve the out-of-focus issue in microscopy, we developed a Cycle Generative Adversarial Network (CycleGAN) based model and a multi-component weighted loss function.

4
26 Apr 2022

BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix

bupt-ai-cz/BCI 25 Apr 2022

The evaluation of human epidermal growth factor receptor 2 (HER2) expression is essential to formulate a precise treatment for breast cancer.

170
25 Apr 2022

Explainable Diabetic Retinopathy Detection and Retinal Image Generation

zzdyyy/Patho-GAN 1 Jul 2021

Though deep learning has shown successful performance in classifying the label and severity stage of certain diseases, most of them give few explanations on how to make predictions.

63
01 Jul 2021

Overcoming Barriers to Data Sharing with Medical Image Generation: A Comprehensive Evaluation

AugustDS/synthetic-medical-benchmark 29 Nov 2020

Our study offers valuable guidelines and outlines practical conditions under which insights derived from synthetic medical images are similar to those that would have been derived from real imaging data.

18
29 Nov 2020

MammoGANesis: Controlled Generation of High-Resolution Mammograms for Radiology Education

cyrilzakka/stylegan2-tpu 11 Oct 2020

During their formative years, radiology trainees are required to interpret hundreds of mammograms per month, with the objective of becoming apt at discerning the subtle patterns differentiating benign from malignant lesions.

35
11 Oct 2020

Evaluating the Clinical Realism of Synthetic Chest X-Rays Generated Using Progressively Growing GANs

BradSegal/CXR_PGGAN 7 Oct 2020

We apply a PGGAN to the task of unsupervised x-ray synthesis and have radiologists evaluate the clinical realism of the resultant samples.

13
07 Oct 2020

Image Translation for Medical Image Generation -- Ischemic Stroke Lesions

MoPl90/image_translation 5 Oct 2020

We demonstrate with the example of ischemic stroke that an improvement in lesion segmentation is feasible using deep learning based augmentation.

2
05 Oct 2020

Melanoma Detection using Adversarial Training and Deep Transfer Learning

hasibzunair/adversarial-lesions Journal of Physics in Medicine and Biology 2020

In the first stage, we leverage the inter-class variation of the data distribution for the task of conditional image synthesis by learning the inter-class mapping and synthesizing under-represented class samples from the over-represented ones using unpaired image-to-image translation.

29
14 Apr 2020

ADN: Artifact Disentanglement Network for Unsupervised Metal Artifact Reduction

liaohaofu/adn 3 Aug 2019

Current deep neural network based approaches to computed tomography (CT) metal artifact reduction (MAR) are supervised methods that rely on synthesized metal artifacts for training.

156
03 Aug 2019

Skin Lesion Synthesis with Generative Adversarial Networks

alceubissoto/gan-skin-lesion 8 Feb 2019

Skin cancer is by far the most common type of cancer.

39
08 Feb 2019