Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization

Generative adversarial networks (GANs) have ushered in a revolution in image-to-image translation. The development and proliferation of GANs raises an interesting question: can we train a GAN to remove an object, if present, from an image while otherwise preserving the image? Specifically, can a GAN "virtually heal" anyone by turning his medical image, with an unknown health status (diseased or healthy), into a healthy one, so that diseased regions could be revealed by subtracting those two images? Such a task requires a GAN to identify a minimal subset of target pixels for domain translation, an ability that we call fixed-point translation, which no GAN is equipped with yet. Therefore, we propose a new GAN, called Fixed-Point GAN, trained by (1) supervising same-domain translation through a conditional identity loss, and (2) regularizing cross-domain translation through revised adversarial, domain classification, and cycle consistency loss. Based on fixed-point translation, we further derive a novel framework for disease detection and localization using only image-level annotation. Qualitative and quantitative evaluations demonstrate that the proposed method outperforms the state of the art in multi-domain image-to-image translation and that it surpasses predominant weakly-supervised localization methods in both disease detection and localization. Implementation is available at https://github.com/jlianglab/Fixed-Point-GAN.


page 12

page 13

page 14

page 15

page 16

page 17

page 18

page 19


Asymmetric Generative Adversarial Networks for Image-to-Image Translation

State-of-the-art models for unpaired image-to-image translation with Gen...

A Generalized Framework for Critical Heat Flux Detection Using Unsupervised Image-to-Image Translation

This work proposes a framework developed to generalize Critical Heat Flu...

3D-Aware Multi-Class Image-to-Image Translation with NeRFs

Recent advances in 3D-aware generative models (3D-aware GANs) combined w...

DualGAN: Unsupervised Dual Learning for Image-to-Image Translation

Conditional Generative Adversarial Networks (GANs) for cross-domain imag...

Rethinking CycleGAN: Improving Quality of GANs for Unpaired Image-to-Image Translation

An unpaired image-to-image (I2I) translation technique seeks to find a m...

Twin-GAN -- Unpaired Cross-Domain Image Translation with Weight-Sharing GANs

We present a framework for translating unlabeled images from one domain ...

Style-Restricted GAN: Multi-Modal Translation with Style Restriction Using Generative Adversarial Networks

Unpaired image-to-image translation using Generative Adversarial Network...

Please sign up or login with your details

Forgot password? Click here to reset