A slice classification neural network for automated classification of axial PET/CT slices from a multi-centric lymphoma dataset

arXiv:2403.07105v1 Announce Type: cross
Abstract: Automated slice classification is clinically relevant since it can be incorporated into medical image segmentation workflows as a preprocessing step that would flag slices with a higher probability of containing tumors, thereby directing physicians attention to the important slices. In this work, we train a ResNet-18 network to classify axial slices of lymphoma PET/CT images (collected from two institutions) depending on whether the slice intercepted a tumor (positive slice) in the 3D image or if …

abstract arxiv attention automated classification cs.cv cs.lg dataset eess.iv image medical network neural network pet physicians physics.med-ph probability segmentation slice tumors type workflows