Surgical data science is devoted to enhancing the quality, safety, and efficacy of
interventional healthcare. While the use of powerful machine learning algorithms is …

Endoscopy is a widely used technique for the early detection of diseases or robotic-assisted
minimally invasive surgery (RMIS). Numerous deep learning (DL)-based research works …

Surgery requires comprehensive medical knowledge, visual assessment skills, and
procedural expertise. While recent surgical AI models have focused on solving task-specific …

In the realm of robot-assisted minimally invasive surgery, dynamic scene reconstruction can
significantly enhance downstream tasks and improve surgical outcomes. Neural Radiance …

The absence of openly accessible data and specialized foundation models is a major barrier
for computational research in surgery. Toward this,(i) we open-source the largest dataset of …

Considering that coupled dictionary learning (CDL) method can obtain a reasonable linear
mathematical relationship between resource images, we propose a novel CDL-based …

As a prominent subfield of Artificial Intelligence Generated Content (AIGC), video generation
has achieved notable advancements in recent years. The introduction of Sora-alike models …

Navigation assistance has become part of our daily lives and its implementation in medicine
has been going on for the last 3 decades. Navigation is defined as the determination of a …

Foundation models have revolutionized computer vision by achieving vastly superior
performance across diverse tasks through large-scale pretraining on extensive datasets …

Instance segmentation of surgical instruments is a long-standing research problem, crucial
for the development of many applications for computer-assisted surgery. This problem is …