Search Results for author: Robert Grupp

Found 6 papers, 2 papers with code

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

1 code implementation16 Nov 2019 Robert Grupp, Mathias Unberath, Cong Gao, Rachel Hegeman, Ryan Murphy, Clayton Alexander, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor

By using these annotations as training data for neural networks, state of the art performance in fluoroscopic segmentation and landmark localization was achieved.

Anatomy

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

no code implementations22 Oct 2019 Robert Grupp, Ryan Murphy, Rachel Hegeman, Clayton Alexander, Mathias Unberath, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor

The relative pose of the fragment is established by estimating the movement of the two BB constellations using a single fluoroscopic view taken after osteotomy and fragment relocation.

Pose Estimation

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

1 code implementation23 Sep 2019 Robert Grupp, Mehran Armand, Russell Taylor

We use intensity-based 2D/3D registration to estimate the pelvis pose with respect to fluoroscopic images, recover relative poses of multiple views, and triangulate landmarks which may be used for navigation.

Smooth Extrapolation of Unknown Anatomy via Statistical Shape Models

no code implementations23 Sep 2019 Robert Grupp, Hsin-Hong Chiang, Yoshito Otake, Ryan Murphy, Chad Gordon, Mehran Armand, Russell Taylor

The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface.

Anatomy

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

no code implementations23 Sep 2019 Robert Grupp, Yoshito Otake, Ryan Murphy, Javad Parvizi, Mehran Armand, Russell Taylor

In order to reduce radiation exposure, we propose a new smooth extrapolation method leveraging a partial pelvis CT and a statistical shape model (SSM) of the full pelvis in order to estimate a patient's complete pelvis.

Anatomy

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