March 14, 2024, 4:46 a.m. | Tiange Xiang, Yixiao Zhang, Yongyi Lu, Alan Yuille, Chaoyi Zhang, Weidong Cai, Zongwei Zhou

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.08689v1 Announce Type: cross
Abstract: Radiography imaging protocols focus on particular body regions, therefore producing images of great similarity and yielding recurrent anatomical structures across patients. Exploiting this structured information could potentially ease the detection of anomalies from radiography images. To this end, we propose a Simple Space-Aware Memory Matrix for In-painting and Detecting anomalies from radiography images (abbreviated as SimSID). We formulate anomaly detection as an image reconstruction task, consisting of a space-aware memory matrix and an in-painting block …

anomaly anomaly detection arxiv cs.cv detection eess.iv images type unsupervised

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