Fundus to Angiography Generation
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Benchmarks
Most implemented
Image-to-Image Translation with Conditional Adversarial Networks
U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
StarGAN v2: Diverse Image Synthesis for Multiple Domains
Papers
VTGAN: Semi-supervised Retinal Image Synthesis and Disease Prediction using Vision Transformers
In Fluorescein Angiography (FA), an exogenous dye is injected in the bloodstream to image the vascular structure of the retina. The injected dye can cause adverse reactions such as nausea, vomiting, anaphylactic shock, a…
Disease PredictionFundus to Angiography GenerationGenerative Adversarial NetworkImage GenerationAttention2AngioGAN: Synthesizing Fluorescein Angiography from Retinal Fundus Images using Generative Adversarial Networks
Fluorescein Angiography (FA) is a technique that employs the designated camera for Fundus photography incorporating excitation and barrier filters. FA also requires fluorescein dye that is injected intravenously, which m…
Fundus to Angiography GenerationTranslationFundus2Angio: A Conditional GAN Architecture for Generating Fluorescein Angiography Images from Retinal Fundus Photography
Carrying out clinical diagnosis of retinal vascular degeneration using Fluorescein Angiography (FA) is a time consuming process and can pose significant adverse effects on the patient. Angiography requires insertion of a…
Fundus to Angiography GenerationGenerative Adversarial NetworkStarGAN v2: Diverse Image Synthesis for Multiple Domains
A good image-to-image translation model should learn a mapping between different visual domains while satisfying the following properties: 1) diversity of generated images and 2) scalability over multiple domains. Existi…
DiversityFundus to Angiography GenerationImage GenerationImage-to-Image Translation+2U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation
We propose a novel method for unsupervised image-to-image translation, which incorporates a new attention module and a new learnable normalization function in an end-to-end manner. The attention module guides our model t…
Fundus to Angiography GenerationImage-to-Image TranslationTranslationUnsupervised Image-To-Image TranslationHigh-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs
We present a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks (conditional GANs). Conditional GANs have enabled a variety of ap…
Conditional Image GenerationFundus to Angiography GenerationImage GenerationImage-to-Image Translation+5