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

Endovascular techniques have been embraced as a minimally-invasive treatment approach
within different disciplines of interventional radiology and cardiology. The current practice of …

Objective: State-of-the-art techniques for surgical data analysis report promising results for
automated skill assessment and action recognition. The contributions of many of these …

Background Rising health and financial costs associated with iatrogenic errors have drawn
increasing attention to the dexterity of surgeons. With the advent of new technologies, such …

In recent years, digital endoscopy has established as key technology for medical screenings
and minimally invasive surgery. Since then, various research communities with manifold …

Training skillful and competent surgeons is critical to ensure high quality of care and to
minimize disparities in access to effective care. Traditional models to train surgeons are …

We consider the problem of classifying surgical gestures and skill level in robotic surgical
tasks. Prior work in this area models gestures as states of a hidden Markov model (HMM) …

Much of the existing work on automatic classification of gestures and skill in robotic surgery
is based on dynamic cues (eg, time to completion, speed, forces, torque) or kinematic data …

Modeling and analyzing surgeries based on signals that are obtained automatically from the
operating room (OR) is a field of recent interest. It can be valuable for analyzing and …

Automatic surgical gesture segmentation and recognition can provide useful feedback for
surgical training in robotic surgery. Most prior work in this field relies on the robot's kinematic …