Robotic-assisted surgery is now well established in clinical practice and has become the
gold-standard clinical treatment option for several clinical indications. The field of robotic …

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 …

Gastrointestinal (GI) pathologies are periodically screened, biopsied, and resected using
surgical tools. Usually, the procedures and the treated or resected areas are not specifically …

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

Intraoperative tracking of laparoscopic instruments is often a prerequisite for computer and
robotic-assisted interventions. While numerous methods for detecting, segmenting and …

Deep learning in gastrointestinal endoscopy can assist to improve clinical performance and
be helpful to assess lesions more accurately. To this extent, semantic segmentation methods …

Surgical-tool joint detection from laparoscopic images is an important but challenging task in
computer-assisted minimally invasive surgery. Illumination levels, variations in background …

We study the task of semantic segmentation of surgical instruments in robotic-assisted
surgery scenes. We propose the Instance-based Surgical Instrument Segmentation Network …

In this letter, we describe a novel framework for planning and executing semi-autonomous
tissue retraction in minimally invasive robotic surgery. The approach is aimed at removing …

Automatic surgical instrument segmentation of endoscopic images is a crucial building block
of many computer-assistance applications for minimally invasive surgery. So far, state-of-the …