Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …

Cancer, characterized by the uncontrolled division of abnormal cells that harm body tissues,
necessitates early detection for effective treatment. Medical imaging is crucial for identifying …

Precise image segmentation provides clinical study with meaningful and well-structured
information. Despite the remarkable progress achieved in medical image segmentation …

Based on deep learning, pancreatic cancer pathology image segmentation technology
effectively assists pathologists in achieving improved treatment outcomes. However …

Liver plays an important role in metabolic processes, therefore fast diagnosis and potential
surgical planning is essential in case of any disease. The automatic liver segmentation …

Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly
supported by multi-modal large language models (MLLMs). However, previous research has …

Volume reconstruction techniques are gaining increasing interest in medical domains due to
their potential to learn complex 3D structural information from sparse 2D images. Recently …

The global significance of diagnosing liver diseases is heightened, particularly in under-
resourced regions with limited healthcare facilities. Traditional diagnostic methods …

Globally liver diseases are the most life-threatening diseases, and according to global
cancer statistics, liver cancer is the most common. Early detection of liver cancer can prevent …

The scarcity of annotations poses a significant challenge in medical image analysis. Large-
scale pre-training has emerged as a promising label-efficient solution, owing to the …