activity
20162023
most citedPlan in 2D, execute in 3D: An augmented reality solution for cup placement in total hip arthroplasty

36 citations · 119 across the 19 of their papers we have counts for

collaborators
Showing 2019 · cs.CVShow all

9 papers · 2 filters

cs.CV2019

Automatic Annotation of Hip Anatomy in Fluoroscopy for Robust and Efficient 2D/3D Registration

Robert Grupp, Mathias Unberath, Cong Gao +7

Fluoroscopy is the standard imaging modality used to guide hip surgery and is therefore a natural sensor for computer-assisted navigation. In order to efficiently solve the complex…

cs.CV2019

Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy

Robert Grupp, Ryan Murphy, Rachel Hegeman +6

Accurate and consistent mental interpretation of fluoroscopy to determine the position and orientation of acetabular bone fragments in 3D space is difficult. We propose a computer…

cs.CV2019★ 3 cited

Pelvis Surface Estimation From Partial CT for Computer-Aided Pelvic Osteotomies

Robert Grupp, Yoshito Otake, Ryan Murphy +3

Computer-aided surgical systems commonly use preoperative CT scans when performing pelvic osteotomies for intraoperative navigation. These systems have the potential to improve the…

cs.CV2019★ 18 cited

Patch-Based Image Similarity for Intraoperative 2D/3D Pelvis Registration During Periacetabular Osteotomy

Robert Grupp, Mehran Armand, Russell Taylor

Periacetabular osteotomy is a challenging surgical procedure for treating developmental hip dysplasia, providing greater coverage of the femoral head via relocation of a patient's…

cs.CV2019★ 2 cited

Smooth Extrapolation of Unknown Anatomy via Statistical Shape Models

Robert Grupp, Hsin-Hong Chiang, Yoshito Otake +4

Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical…

cs.CV2019

Self-supervised Dense 3D Reconstruction from Monocular Endoscopic Video

Xingtong Liu, Ayushi Sinha, Masaru Ishii +3

We present a self-supervised learning-based pipeline for dense 3D reconstruction from full-length monocular endoscopic videos without a priori modeling of anatomy or shading. Our m…