Deep Reinforcement Learning for the Control of Robotic Manipulation: A Focussed Mini-Review
Deep learning has provided new ways of manipulating, processing and analyzing data. It sometimes may achieve results comparable to, or surpassing human expert performance, and has become a source...
Spatiotemporal modeling of grip forces captures proficiency in manual robot control
This paper builds on our previous work by exploiting Artificial Intelligence to predict individual grip force variability in manual robot control. Grip forces were recorded from various loci in...
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. The...
Using spatial-temporal ensembles of convolutional neural networks for lumen segmentation in ureteroscopy
Purpose: Ureteroscopy is an efficient endoscopic minimally invasive technique for the diagnosis and treatment of upper tract urothelial carcinoma (UTUC). During ureteroscopy, the automatic...
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation
Person detection and pose estimation is a key requirement to develop intelligent context-aware assistance systems. To foster the development of human pose estimation methods and their applications...
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
Surgical workflow recognition has numerous potential medical applications, such as the automatic indexing of surgical video databases and the optimization of real-time operating room scheduling,...
A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture
Ureteroscopy is becoming the first surgical treatment option for the majority of urinary affections. This procedure is performed using an endoscope which provides the surgeon with the visual...
Sensors for expert grip force profiling: towards benchmarking manual control of a robotic device for surgical tool movements
STRAS (Single access Transluminal Robotic Assistant for Surgeons) is a new robotic system for application to intraluminal surgical procedures. Preclinical testing of STRAS has recently permitted...
A transfer-learning approach for lesion detection in endoscopic images from the urinary tract
Ureteroscopy and cystoscopy are the gold standard methods to identify and treat tumors along the urinary tract. It has been reported that during a normal procedure a rate of 10-20 % of the lesions...
A Multi-view RGB-D Approach for Human Pose Estimation in Operating Rooms
Many approaches have been proposed for human pose estimation in single and multi-view RGB images. However, some environments, such as the operating room, are still very challenging for...
Wearable Sensors for Spatio-Temporal Grip Force Profiling
Wearable biosensor technology enables real-time, convenient, and continuous monitoring of users behavioral signals. Such include signals relative to body motion, body temperature, biological or...
Correlating grip force signals from multiple sensors highlights prehensile control strategies in a complex task-user system
Wearable sensor systems with transmitting capabilities are currently employed for the biometric screening of exercise activities and other performance data. Such technology is generally wireless...
Single- and Multi-Task Architectures for Surgical Workflow Challenge at M2CAI 2016
The surgical workflow challenge at M2CAI 2016 consists of identifying 8 surgical phases in cholecystectomy procedures. Here, we propose to use deep architectures that are based on our previous...
Single- and Multi-Task Architectures for Tool Presence Detection Challenge at M2CAI 2016
The tool presence detection challenge at M2CAI 2016 consists of identifying the presence/absence of seven surgical tools in the images of cholecystectomy videos. Here, we propose to use deep...
Articulated Clinician Detection Using 3D Pictorial Structures on RGB-D Data
Reliable human pose estimation (HPE) is essential to many clinical applications, such as surgical workflow analysis, radiation safety monitoring and human-robot cooperation. Proposed methods for...