Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction-Reference-Cited by-同舟云学术

Simurgh: A Framework for Cad-Driven Deep Learning Based X-Ray CT Reconstruction

Published:2022-10-16 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Image Processing (ICIP)
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Author:

Ziabari Amirkoushyar¹,Venkatakrishnan Singanallur¹,Dubey Abhishek¹,Lisovich Alex²,Brackman Paul²,Frederick Curtis²,Bhattad Pradeep²,Bingham Philip¹,Plotkowski Alex¹,Dehoff Ryan¹,Paquit Vincent¹

Affiliation:

1. Oak Ridge National Lab (ORNL),Oak Ridge,TN,37830

2. Carl Zeiss Industrial Metrology,LLC,Maple Grove,MN,USA,55369

Funder

U.S. Department of Energy

Office of Energy

Advanced Manufacturing Office

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9897158/9897159/09898017.pdf?arnumber=9898017

Reference21 articles.

1. CAD-Based Scatter Compensation For Polychromatic Reconstruction Of Additive Manufactured Parts

2. Beam Hardening Artifact Reduction in X-Ray CT Reconstruction of 3D Printed Metal Parts Leveraging Deep Learning and CAD Models

3. An energy-based beam hardening model in tomography

4. CAD-based x-ray CT calibration and error compensation

5. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

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