Recent developments in data science in general and machine learning in particular have
transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a …

Accurate and objective performance assessment is essential for both trainees and certified
surgeons. However, existing methods can be time consuming, labor intensive, and subject …

Medical image analysis plays an important role in clinical diagnosis. In this paper, we
examine the recent Segment Anything Model (SAM) on medical images, and report both …

Medical vision-language models (VLMs) combine computer vision (CV) and natural
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …

The Segment Anything Model (SAM) is a powerful foundation model that has revolutionised
image segmentation. To apply SAM to surgical instrument segmentation, a common …

Due to the inherent flexibility of prompting, foundation models have emerged as the
predominant force in the fields of natural language processing and computer vision. The …

Surgical robots have been widely adopted with over 4000 robots being used in practice
daily. However, these are telerobots that are fully controlled by skilled human surgeons …

Abstract The Segment Anything Model (SAM) serves as a fundamental model for semantic
segmentation and demonstrates remarkable generalization capabilities across a wide range …

We present our novel deep multi-task learning method for medical image segmentation.
Existing multi-task methods demand ground truth annotations for both the primary and …

Data-driven computational approaches have evolved to enable extraction of information
from medical images with reliability, accuracy, and speed, which is already transforming …