Unsupervised anomaly detection in medical images with a memory-augmented multi-level cross-attentional masked autoencoder

• Main Authors: TIAN, Yu, PANG, Guansong, LIU, Yuyuan, WANG, Chong, CHEN, Yuanhong, LIU, Fengbei, SINGH, Rajvinder, VERJANS, Johan W., WANG, Mengyu, CARNEIRO, Gustavo
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Pneumonia; Covid-19; Colonoscopy; Unsupervised Learning; Anomaly Detection' Anomaly Segmentation; Vision Transformer; Artificial Intelligence and Robotics; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8329; https://ink.library.smu.edu.sg/context/sis_research/article/9332/viewcontent/UnsupervisedAnomaly_av.pdf
• Institution: Singapore Management University

Unsupervised anomaly detection (UAD) aims to find anomalous images by optimising a detector using a training set that contains only normal images. UAD approaches can be based on reconstruction methods, self-supervised approaches, and Imagenet pre-trained models. Reconstruction methods, which detect...