A review on deep learning in minimally invasive surgery

I Rivas-Blanco, CJ Perez-Del-Pulgar… - IEEE …, 2021 - ieeexplore.ieee.org
In the last five years, deep learning has attracted great interest in computer-assisted systems
for Minimally Invasive Surgery. The straightforward accessibility to images in surgical …

Myocardial involvement after hospitalization for COVID-19 complicated by troponin elevation: a prospective, multicenter, observational study

J Artico, H Shiwani, JC Moon, M Gorecka, GP McCann… - Circulation, 2023 - Am Heart Assoc
Background: Acute myocardial injury in hospitalized patients with coronavirus disease 2019
(COVID-19) has a poor prognosis. Its associations and pathogenesis are unclear. Our aim …

Methods and datasets for segmentation of minimally invasive surgical instruments in endoscopic images and videos: A review of the state of the art

T Rueckert, D Rueckert, C Palm - Computers in Biology and Medicine, 2024 - Elsevier
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 …

Sam meets robotic surgery: an empirical study on generalization, robustness and adaptation

A Wang, M Islam, M Xu, Y Zhang, H Ren - International Conference on …, 2023 - Springer
Abstract The Segment Anything Model (SAM) serves as a fundamental model for semantic
segmentation and demonstrates remarkable generalization capabilities across a wide range …

Fun-sis: A fully unsupervised approach for surgical instrument segmentation

L Sestini, B Rosa, E De Momi, G Ferrigno… - Medical Image Analysis, 2023 - Elsevier
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 …

SurgiNet: Pyramid attention aggregation and class-wise self-distillation for surgical instrument segmentation

ZL Ni, XH Zhou, GA Wang, WQ Yue, Z Li, GB Bian… - Medical Image …, 2022 - Elsevier
Surgical instrument segmentation plays a promising role in robot-assisted surgery. However,
illumination issues often appear in surgical scenes, altering the color and texture of surgical …

Surgical tool datasets for machine learning research: a survey

M Rodrigues, M Mayo, P Patros - International Journal of Computer Vision, 2022 - Springer
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 …

MSDESIS: Multitask stereo disparity estimation and surgical instrument segmentation

D Psychogyios, E Mazomenos… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Reconstructing the 3D geometry of the surgical site and detecting instruments within it are
important tasks for surgical navigation systems and robotic surgery automation. Traditional …

Scanpathnet: A recurrent mixture density network for scanpath prediction

RAJ de Belen, T Bednarz… - Proceedings of the IEEE …, 2022 - openaccess.thecvf.com
Understanding the mechanisms underlying human visual attention is an important research
problem in cognitive neuroscience and computer vision. While existing models predict …

Space squeeze reasoning and low-rank bilinear feature fusion for surgical image segmentation

ZL Ni, GB Bian, Z Li, XH Zhou, RQ Li… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Surgical image segmentation is critical for surgical robot control and computer-assisted
surgery. In the surgical scene, the local features of objects are highly similar, and the …