3 papers
cs.CV2024
Revisiting Deep Ensemble Uncertainty for Enhanced Medical Anomaly Detection
Yi Gu, Yi Lin, Kwang-Ting Cheng +1
Medical anomaly detection (AD) is crucial in pathological identification and localization. Current methods typically rely on uncertainty estimation in deep ensembles to detect anom…
cs.CV2024
Aligning Medical Images with General Knowledge from Large Language Models
Xiao Fang, Yi Lin, Dong Zhang +2
Pre-trained large vision-language models (VLMs) like CLIP have revolutionized visual representation learning using natural language as supervisions, and demonstrated promising gene…
cs.LG2024
Rethinking Autoencoders for Medical Anomaly Detection from A Theoretical Perspective
Yu Cai, Hao Chen, Kwang-Ting Cheng
Medical anomaly detection aims to identify abnormal findings using only normal training data, playing a crucial role in health screening and recognizing rare diseases. Reconstructi…