Search Results for author: Peter Gehlbach

Found 4 papers, 1 papers with code

Y-Net: A Spatiospectral Dual-Encoder Networkfor Medical Image Segmentation

1 code implementation15 Apr 2022 Azade Farshad, Yousef Yeganeh, Peter Gehlbach, Nassir Navab

Automated segmentation of retinal optical coherence tomography (OCT) images has become an important recent direction in machine learning for medical applications.

 Ranked #1 on Retinal OCT Layer Segmentation on Duke SD-OCT (using extra training data)

Image Segmentation Medical Image Segmentation +3

Autonomously Navigating a Surgical Tool Inside the Eye by Learning from Demonstration

no code implementations16 Nov 2020 Ji Woong Kim, Changyan He, Muller Urias, Peter Gehlbach, Gregory D. Hager, Iulian Iordachita, Marin Kobilarov

We show that the network can reliably navigate a needle surgical tool to various desired locations within 137 microns accuracy in physical experiments and 94 microns in simulation on average, and generalizes well to unseen situations such as in the presence of auxiliary surgical tools, variable eye backgrounds, and brightness conditions.

Autonomous Navigation Depth Estimation +1

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