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Found 19 papers, 2 papers with code
SAF-IS: a Spatial Annotation Free Framework for Instance Segmentation of Surgical Tools
In this work, we develop a framework for instance segmentation not relying on spatial annotations for training.
Uncertainty-aware Self-supervised Learning for Cross-domain Technical Skill Assessment in Robot-assisted Surgery
In this paper, we propose a novel approach for skill assessment by transferring domain knowledge from labeled kinematic data to unlabeled data.
Markerless 3D human pose tracking through multiple cameras and AI: Enabling high accuracy, robustness, and real-time performance
Tracking 3D human motion in real-time is crucial for numerous applications across many fields.
A Unified Architecture for Dynamic Role Allocation and Collaborative Task Planning in Mixed Human-Robot Teams
The growing deployment of human-robot collaborative processes in several industrial applications, such as handling, welding, and assembly, unfolds the pursuit of systems which are able to manage large heterogeneous teams and, at the same time, monitor the execution of complex tasks.
Semi-supervised Bladder Tissue Classification in Multi-Domain Endoscopic Images
We address the challenge of tissue classification when annotations are available only in one domain, in our case WLI, and the endoscopic images correspond to an unpaired dataset, i. e. there is no exact equivalent for every image in both NBI and WLI domains.
Learning-Based Keypoint Registration for Fetoscopic Mosaicking
This surgery is minimally invasive and relies on fetoscopy.
Autonomous Intraluminal Navigation of a Soft Robot using Deep-Learning-based Visual Servoing
Navigation inside luminal organs is an arduous task that requires non-intuitive coordination between the movement of the operator's hand and the information obtained from the endoscopic video.
Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings
For this challenge, we released a dataset of 2060 images, pixel-annotated for vessels, tool, fetus and background classes, from 18 in-vivo TTTS fetoscopy procedures and 18 short video clips.
Open-VICO: An Open-Source Gazebo Toolkit for Vision-based Skeleton Tracking in Human-Robot Collaboration
Simulation tools are essential for robotics research, especially for those domains in which safety is crucial, such as Human-Robot Collaboration (HRC).
FUN-SIS: a Fully UNsupervised approach for Surgical Instrument Segmentation
We then use the obtained instrument masks as pseudo-labels in order to train a per-frame segmentation model; to this aim, we develop a learning-from-noisy-labels architecture, designed to extract a clean supervision signal from these pseudo-labels, leveraging their peculiar noise properties.
FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Dataset
Through the \textit{Fetoscopic Placental Vessel Segmentation and Registration (FetReg)} challenge, we present a large-scale multi-centre dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms for the fetal environment with a focus on creating drift-free mosaics from long duration fetoscopy videos.
An Integrated Dynamic Method for Allocating Roles and Planning Tasks for Mixed Human-Robot Teams
This paper proposes a novel integrated dynamic method based on Behavior Trees for planning and allocating tasks in mixed human robot teams, suitable for manufacturing environments.
A transfer-learning approach for lesion detection in endoscopic images from the urinary tract
In this work we study the implementation of 3 different Convolutional Neural Networks (CNNs), using a 2-steps training strategy, to classify images from the urinary tract with and without lesions.
Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy
Of these, two architectures are taken as core-models, namely U-Net based in residual blocks($m_1$) and Mask-RCNN($m_2$), which are fed with single still-frames $I(t)$.
Robotic needle steering in deformable tissues with extreme learning machines
Control strategies for robotic needle steering in soft tissues must account for complex interactions between the needle and the tissue to achieve accurate needle tip positioning.
A Kinematic Bottleneck Approach For Pose Regression of Flexible Surgical Instruments directly from Images
3-D pose estimation of instruments is a crucial step towards automatic scene understanding in robotic minimally invasive surgery.
A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture
For the training of these networks, we analyze the use of two different color spaces: gray-scale and RGB data images.
Comparison of different CNNs for breast tumor classification from ultrasound images
The best performance was obtained by fine tuning VGG-16, with an accuracy of 0. 919 and an AUC of 0. 934.
Weakly Supervised Recognition of Surgical Gestures
Hence, the potential of weak supervision could be to improve unsupervised learning while avoiding manual annotation of large datasets.
