The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is
propelled by the growing availability of computed tomography (CT) datasets with detailed …

Accurate pancreatic tumor segmentation in CT images is crucial but challenging due to the
complex anatomy and varied tumor appearance. Previous methods predominantly adopt …

Existing promptable segmentation methods in the medical imaging field primarily consider
either textual or visual prompts to segment relevant objects, yet they often fall short when …

Analysis of 3D segmentation models, especially in the context of medical imaging, is often
limited to segmentation performance metrics that overlook the crucial aspect of explainability …

AI-driven tumor analysis has garnered increasing attention in healthcare. However, its
progress is significantly hindered by the lack of annotated tumor cases, which requires …

Medical image segmentation is crucial for diagnostics and treatment planning, yet traditional
methods often struggle with the variability of real-world clinical data. Deep learning models …