60 citations · 78 across the 4 of their papers we have counts for
4 papers
Fully Differentiable Bidirectional Dual-Task Synergistic Learning for Semi-Supervised 3D Medical Image Segmentation
Jun Li
Semi-supervised learning relaxes the need of large pixel-wise labeled datasets for image segmentation by leveraging unlabeled data. The scarcity of high-quality labeled data remain…
Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework
Jun Li, Hongzhang Zhu, Tao Chen +1
Recently, numerous pancreas segmentation methods have achieved promising performance on local single-source datasets. However, these methods don't adequately account for generaliza…
A Dual-Task Synergy-Driven Generalization Framework for Pancreatic Cancer Segmentation in CT Scans
Jun Li, Yijue Zhang, Haibo Shi +3
Pancreatic cancer, characterized by its notable prevalence and mortality rates, demands accurate lesion delineation for effective diagnosis and therapeutic interventions. The gener…
Pancreas segmentation with probabilistic map guided bi-directional recurrent UNet
Jun Li, Xiaozhu Lin, Hui Che +2
Pancreas segmentation in medical imaging data is of great significance for clinical pancreas diagnostics and treatment. However, the large population variations in the pancreas sha…