Synthesizing Diagnostic Burn Images For Deep Learning Applications-Reference-Cited by-同舟云学术

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Synthesizing Diagnostic Burn Images For Deep Learning Applications

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 Annual Modeling and Simulation Conference (ANNSIM)
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Author:

Schenkenfelder Bernhard¹,Kaltenleithner Sophie¹,Sabrowsky-Hirsch Bertram¹,Klug Christoph¹,Lumenta David B.²,Scharinger Josef³

Affiliation:

1. RISC Software GmbH Softwarepark 32a,Department of Medical Informatics,Hagenberg,AUSTRIA

2. Medical University of Graz Auenbruggerplatz 5,Research Unit Digital Surgery Div. of Plastic, Aesthetic and Reconstructive Surgery,Department of Surgery,Graz,AUSTRIA

3. Institute of Computational Perception Johannes Kepler University Altenberger Straße 69,Linz,AUSTRIA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9859263/9859270/09859295.pdf?arnumber=9859295

Reference43 articles.

1. Inter-rater agreement in glioma segmentations on longitudinal MRI

2. Learning from Synthetic Humans

3. A survey on Image Data Augmentation for Deep Learning

4. Elastic Registration of Abdominal MRI Scans and RGB-D Images to Improve Surgical Planning of Breast Reconstruction

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Synthetic Training Data in AI-Driven Quality Inspection: The Significance of Camera, Lighting, and Noise Parameters;Sensors;2024-01-19

2. Dense Mesh RCNN: assessment of human skin burn and burn depth severity;The Journal of Supercomputing;2023-10-04

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