The recent advancements in the surging field of Deep Learning (DL) have revolutionized
every sphere of life, and the healthcare domain is no exception. The enormous success of …

In the field of computer-and robot-assisted minimally invasive surgery, enormous progress
has been made in recent years based on the recognition of surgical instruments in …

Distributed big data and digital healthcare technologies have great potential to promote
medical services, but challenges arise when it comes to learning predictive model from …

This paper is a comprehensive survey of datasets for surgical tool detection and related
surgical data science and machine learning techniques and algorithms. The survey offers a …

Abstract Robotic-Assisted Surgery (RAS) is beginning to unlock its potential. However,
despite the latest advances in RAS, the steep learning curve of RAS devices remains a …

Medical image segmentation and registration are two tasks to analyze the anatomical
structures in clinical research. Still, deep-learning solutions utilizing the connections …

Multiphysics simulation of magnetically actuated origami robots promises a range of
applications such as synthetic data generation, design parameter optimization, predicting …

Minimal invasion is an important trend in surgery. However, the endoscope, as one of the
key devices for monitoring the process of minimally invasive surgery, is limited by its size …

Exoscopes are a promising tool for neurosurgeons, offering improved visualisation and
ergonomics compared with traditional surgical microscopes. They consist of an external …

Surgical instrument segmentation plays a crucial role in robot-assisted surgery by furnishing
essential information about instrument location and orientation. This information not only …