Acquiring Weak Annotations for Tumor Localization in Temporal and Volumetric Data

arXiv:2310.15098v2 Announce Type: replace
Abstract: Creating large-scale and well-annotated datasets to train AI algorithms is crucial for automated tumor detection and localization. However, with limited resources, it is challenging to determine the best type of annotations when annotating massive amounts of unlabeled data. To address this issue, we focus on polyps in colonoscopy videos and pancreatic tumors in abdominal CT scans; both applications require significant effort and time for pixel-wise annotation due to the high dimensional nature of the data, …

abstract ai algorithms algorithms annotations arxiv automated cs.ai cs.cv data datasets detection focus issue localization massive resources scale temporal train train ai type