Recent advances in learning multi-modal representation have witnessed the success in
biomedical domains. While established techniques enable handling multi-modal …

The advent of 3D Gaussian Splatting (3D-GS) techniques and their dynamic scene modeling
variants, 4D-GS, offers promising prospects for real-time rendering of dynamic surgical …

Abstract 3D reconstruction of biological tissues from a collection of endoscopic images is a
key to unlock various important downstream surgical applications with 3D capabilities …

Generating diverse plausible outputs from a single input is crucial for addressing visual
ambiguities, exemplified in medical imaging where experts may provide varying semantic …

Using brain imaging data to predict the non-neuroimaging phenotypes at the individual level
is a fundamental goal of system neuroscience. Despite its significance, the high acquisition …

In the field of intelligent healthcare, the accessibility of medical data is severely constrained
by privacy concerns, high costs, and limited patient cases, significantly hindering automated …

Tooth point cloud segmentation is a fundamental task in many orthodontic applications.
Current research mainly focuses on fully supervised learning which demands expensive …

Accurate landmark detection in medical imaging is essential for quantifying various
anatomical structures and assisting in diagnosis and treatment planning. In ultrasound cine …

Cortical folding is closely linked to brain functions, with gyri acting more like local functional
“hubs” to integrate information than sulci do. However, understanding how anatomical …

Predicting individual-level non-neuroimaging phenotypes (eg, fluid intelligence) using brain
imaging data is a fundamental goal of neuroscience. Recent research has focused on …