Search Results for author:
Found 2 papers, 2 papers with code
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images
Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high costs, time, and effort for annotation.
Ranked #1 on
Anomaly Detection
on ADNI
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease
Therefore, this paper poses the research question of how to improve unsupervised anomaly detection by utilizing (1) an unannotated set of mixed images, in addition to (2) the set of healthy images as being used in the literature.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
