Abstract The Segment Anything Model (SAM), a foundation model for general image
segmentation, has demonstrated impressive zero-shot performance across numerous …

Applying deep learning (DL) for annotating surgical instruments in robot-assisted minimally
invasive surgeries (MIS) represents a significant advancement in surgical technology. This …

In this study, we propose a novel approach for RGB-D salient instance segmentation using a
dual-branch cross-modal feature calibration architecture called CalibNet. Our method …

We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS),
a two-stage, fully transformer-based method that leverages modern pixel-wise attention …

Surgical scene segmentation is a critical task in Robotic-assisted surgery. However, the
complexity of the surgical scene, which mainly includes local feature similarity (eg, between …

Surgical robotics application in the field of minimally invasive surgery has developed rapidly
and has been attracting increasingly more research attention in recent years. A common …

In the realm of automated robotic surgery and computer-assisted interventions,
understanding robotic surgical activities stands paramount. Existing algorithms dedicated to …