2018 robotic scene segmentation challenge
In 2015 we began a sub-challenge at the EndoVis workshop at MICCAI in Munich using
endoscope images of ex-vivo tissue with automatically generated annotations from robot …
endoscope images of ex-vivo tissue with automatically generated annotations from robot …
Synthetic and real inputs for tool segmentation in robotic surgery
Semantic tool segmentation in surgical videos is important for surgical scene understanding
and computer-assisted interventions as well as for the development of robotic automation …
and computer-assisted interventions as well as for the development of robotic automation …
Exploring intra-and inter-video relation for surgical semantic scene segmentation
Automatic surgical scene segmentation is fundamental for facilitating cognitive intelligence
in the modern operating theatre. Previous works rely on conventional aggregation modules …
in the modern operating theatre. Previous works rely on conventional aggregation modules …
Trasetr: track-to-segment transformer with contrastive query for instance-level instrument segmentation in robotic surgery
Surgical instrument segmentation-in general a pixel classification task-is fundamentally
crucial for promoting cognitive intelligence in robot-assisted surgery (RAS). However …
crucial for promoting cognitive intelligence in robot-assisted surgery (RAS). However …
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 …
surgical data science and machine learning techniques and algorithms. The survey offers a …
Matis: Masked-attention transformers for surgical instrument segmentation
We propose Masked-Attention Transformers for Surgical Instrument Segmentation (MATIS),
a two-stage, fully transformer-based method that leverages modern pixel-wise attention …
a two-stage, fully transformer-based method that leverages modern pixel-wise attention …
LSKANet: Long strip kernel attention network for robotic surgical scene segmentation
M Liu, Y Han, J Wang, C Wang, Y Wang… - … on Medical Imaging, 2023 - ieeexplore.ieee.org
Surgical scene segmentation is a critical task in Robotic-assisted surgery. However, the
complexity of the surgical scene, which mainly includes local feature similarity (eg, between …
complexity of the surgical scene, which mainly includes local feature similarity (eg, between …
Task decomposition and synchronization for semantic biomedical image segmentation
Semantic segmentation is essentially important to biomedical image analysis. Many recent
works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with …
works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with …
A comprehensive survey on recent deep learning-based methods applied to surgical data
Minimally invasive surgery is highly operator dependant with a lengthy procedural time
causing fatigue to surgeon and risks to patients such as injury to organs, infection, bleeding …
causing fatigue to surgeon and risks to patients such as injury to organs, infection, bleeding …
LACOSTE: Exploiting stereo and temporal contexts for surgical instrument segmentation
Surgical instrument segmentation is instrumental to minimally invasive surgeries and related
applications. Most previous methods formulate this task as single-frame-based instance …
applications. Most previous methods formulate this task as single-frame-based instance …