AI-Based Automated Lipomatous Tumor Segmentation in MR Images: Ensemble Solution to Heterogeneous Data.

Deep learning (DL) has been proposed to automate image segmentation and provide accuracy, consistency, and efficiency. Accurate segmentation of lipomatous tumors (LTs) is critical for correct tumor radiomics analysis and localization. The major challenge of this task is data heterogeneity, including tumor morphological characteristics and multicenter scanning protocols.

Total-body PET/CT - First Clinical Experiences and Future Perspectives.

Total-body PET has come a long way from its first conception to today, with both total-body and long axial field of view (> 1m) scanners now being commercially available world-wide. The conspicuous signal collection efficiency gain, coupled with high spatial resolution, allows for higher sensitivity and improved lesion detection, enhancing several clinical applications not readily available on current conventional PET/CT scanners. This technology can provide (a) reduction in acquisition times with preservation of diagnostic quality images, benefitting specific clinical situations (i.