Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D Datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains-Reference-Cited by-同舟云学术

Pre- and Post-processing Strategies for Generic Slice-wise Segmentation of Tomographic 3D Datasets Utilizing U-Net Deep Learning Models Trained for Specific Diagnostic Domains

Published:2020 Issue: Volume: Page:
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Container-title:Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications
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Author:

Zwettler Gerald¹,Backfrieder Werner²,Holmes III David³

Affiliation:

1. Biomedical Analytics and Computational Engineering Lab, Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, 200 First St. SW, 55905 Rochester, MN, U.S.A., Research Group Advanced Information Systems and Technology (AIST), Department of Software Engineering, University of Applied Sciences Upper Austria, Softwarepark 11, 4232 Hagenberg, Austria, --- Select a Country ---

2. Medical Informatics, Department of Software Engineering, University of Applied Sciences Upper Austria, Softwarepark 11, 4232 Hagenberg, Austria, --- Select a Country ---

3. Biomedical Analytics and Computational Engineering Lab, Department of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, 200 First St. SW, 55905 Rochester, MN, U.S.A., --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

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