Evaluation of the detection accuracy of a fully automated AI-based lesion segmentation tool in whole-body FDG PET/CT for lymphoma.
BACKGROUND This study evaluated an AI-based lesion segmentation tool using a hybrid 2D-3D deep learning model based on the nnUNet architecture with a ResNet18 backbone, incorporating post-processing to reduce false positives and segmentation-related quantitative errors. METHODS Whole-body FDG PET/CT scans from 72 lym...