GAN-Driven Anomaly Detection for Active Learning in Medical Imaging Segmentation
MD Anderson Cancer Center
January 2020 – Present
Lab Website
The following links contain my writings on the project, both published and unpublished.
2023
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image Segmentation
Interpretable Out-of-Distribution Detection with Generative Adversarial Networks
Interpretable Out-of-Distribution Detection for Medical Images Using Generative Adversarial Networks and the MIDRC Data Repository
2022
StyleGAN2-based Out-of-Distribution Detection for Medical Imaging
Evaluating the Performance of StyleGAN2-ADA on Medical Images
Generative Adversarial Network-based Out-of-Distribution Detection in Medical Imaging
Comparing Transfer Learning, Data Augmentation, and Data Expansion in the Improvement of Medical Image Generation
Improving the Generation of Synthetic Medical Images using Data Augmentation and Transfer Learning
2021
Detecting Out-of-Distribution Images for Active Learning using a Generative Adversarial Network (StyleGAN2)
GAN-Driven Anomaly Detection for Active Learning in Medical Imaging Segmentation