Learning manipulation skills from open surgery provides more flexible access to the organ
targets in the abdomen cavity and this could make the surgical robot working in a highly …

Semantic segmentation of urban scenes is an essential component in various applications
of autonomous driving. It makes great progress with the rise of deep learning technologies …

is an important problem in computer-assisted orthopedic surgery (CAOS). As one typical
example, the pre-operative space where the patient-specific surgical plan is usually made …

Real-time and precise prediction for traffic of networks is critically important for allocating the
optimal computing/network resources based on users' business requirements, analyzing the …

Visual localization is a fundamental capability in robotics and has been well studied for
recent decades. Although many state-of-the-art algorithms have been proposed, great …

This paper introduces a robust generalized point cloud (PC) registration method that utilizes
not only the positional but also the orientation information associated with each point. The …

Abstract Background Optical tracking systems (OTSs) are essential components of many
modern computer assisted orthopaedic surgery (CAOS) systems but patient movement is …

Registration of two-point sets (PSs) is an essential problem in research areas of robotics,
computer vision, measurements, and computer-assisted interventions (CAIs). Registration …

In this paper, we propose a stereo simultaneous localization and mapping (SLAM) method
based on line segments. For the front-end module of SLAM, we designed a novel method …

Estimating the uncertainty in (probabilistic) image registration enables, eg, surgeons to
assess the operative risk based on the trustworthiness of the registered image data. If …