Hepatocellular carcinoma (HCC) is the fifth most common malignancy and the third leading
cause of cancerrelated death worldwide. HCC exhibits strong intertumor heterogeneity …

As healthcare systems around the world face challenges such as escalating costs, limited
access, and growing demand for personalized care, artificial intelligence (AI) is emerging as …

Multi-phase liver contrast-enhanced computed tomography (CECT) images convey the
complementary multi-phase information for liver tumor segmentation (LiTS), which are …

Medical image segmentation plays an important role in medical diagnosis, and has received
extensive attention in recent years. A large number of convolutional neural network based …

In medical imaging, accurate segmentation is crucial to improving diagnosis, treatment, or
both. However, navigating the multitude of available architectures for automatic …

Liver cancer is the sixth most common cancer in the world and the fourth leading cause of
cancer mortality. In unresectable liver cancers, especially hepatocellular carcinoma (HCC) …

Segmenting the liver and liver tumors in computed tomography (CT) images is an important
step toward quantifiable biomarkers for a computer-aided decision-making system and …

Hypopharyngeal cancer (HPC) is a rare disease. Therefore, it is a challenge to automatically
segment HPC tumors and metastatic lymph nodes (HPC risk areas) from medical images …

Multi-modal tumor segmentation exploits complementary information from different
modalities to help recognize tumor regions. Known multi-modal segmentation methods …

The high postoperative recurrence rates in hepatocellular carcinoma (HCC) remain a major
hurdle in its management. Appropriate staging and treatment selection may alleviate the …