2 papers
cs.CV2026
Removing Motion Artifact in MRI by Using a Perceptual Loss Driven Deep Learning Framework
Ziheng Guo, Danqun Zheng, Shuai Li +8
Purpose: Deep learning-based MRI artifact correction methods often demonstrate poor generalization to clinical data. This limitation largely stems from the inability of deep learni…
cs.CV2025
AutoLugano: A Deep Learning Framework for Fully Automated Lymphoma Segmentation and Lugano Staging on FDG-PET/CT
Boyang Pan, Zeyu Zhang, Hongyu Meng +10
Purpose: To develop a fully automated deep learning system, AutoLugano, for end-to-end lymphoma classification by performing lesion segmentation, anatomical localization, and autom…