An Enhanced Synthetic Cystoscopic Environment for Use in Monocular Depth Estimation-Reference-Cited by-同舟云学术

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An Enhanced Synthetic Cystoscopic Environment for Use in Monocular Depth Estimation

Published:2023-07-24 Issue: Volume: Page:
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Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Somers Peter¹,Deutschmann Mario¹,Holdenried-Krafft Simon²,Tovey Samuel³,Schüle Johannes¹,Veil Carina¹,Aslani Valese⁴,Sawodny Oliver¹,Lensch Hendrik P. A.²,Tarín Cristina¹

Affiliation:

1. University of Stuttgart,Institute for System Dynamics,Stuttgart,Germany,70563

2. University of Tübingen,Institute for Computer Graphics,Tübingen,Germany,72074

3. University of Stuttgart,Institute for Computational Physics,Stuttgart,Germany,70569

4. University of Stuttgart,Institute of Applied Optics,Stuttgart,Germany,70569

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10340303.pdf?arnumber=10340303

Reference10 articles.

1. Minimally Invasive Sensors for Transurethral Impedance Spectroscopy

2. The Interpretation of Structure From Motion

3. Stereo Dense Scene Reconstruction and Accurate Localization for Learning-Based Navigation of Laparoscope in Minimally Invasive Surgery

4. A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation

5. Deeper Depth Prediction with Fully Convolutional Residual Networks

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