1 citations · 2 across the 6 of their papers we have counts for
6 papers
Safe Start Regions for Medical Steerable Needle Automation
Janine Hoelscher, Inbar Fried, Spiros Tsalikis +3
Steerable needles are minimally invasive devices that enable novel medical procedures by following curved paths to avoid critical anatomical obstacles. Planning algorithms can be u…
Leveraging Near-Field Lighting for Monocular Depth Estimation from Endoscopy Videos
Akshay Paruchuri, Samuel Ehrenstein, Shuxian Wang +4
Monocular depth estimation in endoscopy videos can enable assistive and robotic surgery to obtain better coverage of the organ and detection of various health issues. Despite promi…
A Dataset of Anatomical Environments for Medical Robots: Modeling Respiratory Deformation
Inbar Fried, Janine Hoelscher, Jason A. Akulian +1
Anatomical models of a medical robot's environment can significantly help guide design and development of a new robotic system. These models can be used for benchmarking motion pla…
Autonomous Medical Needle Steering In Vivo
Alan Kuntz, Maxwell Emerson, Tayfun Efe Ertop +10
The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safe and accurate navigation of a needle…
A Clinical Dataset for the Evaluation of Motion Planners in Medical Applications
Inbar Fried, Jason A. Akulian, Ron Alterovitz
The prospect of using autonomous robots to enhance the capabilities of physicians and enable novel procedures has led to considerable efforts in developing medical robots and incor…
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Andrew L. Beam, Benjamin Kompa, Allen Schmaltz +6
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing. In this article, we present a new set of…