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1
Introduction
2
Outline
3
Xray CT
4
Xray Scatter
5
Conventional CT
6
Scatter
7
Softwarebased methods
8
Scatter modeling
9
Scatter estimation
10
New features
11
Line integral projections
12
Filter H
13
Neural Network
14
Training Network
15
Results
16
Results in 3D
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Results in Con Beam
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Conclusion
19
Model perturbations
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Worst case perturbations
21
Training schematic
22
Quantitative results
23
Small structure error
24
Small detail error
25
Take home
26
In conclusion
27
Minimax problem
28
Generalizability
Description:
Join a webinar featuring Professor Yoram Bresler from the University of Illinois at Urbana-Champaign as he delves into the world of X-ray Computed Tomography (CT) and scatter correction techniques. Explore conventional CT methods and software-based approaches for scatter modeling and estimation. Discover new features in CT imaging, including line integral projections and neural network applications. Examine the results of these techniques in both 3D and cone beam scenarios. Gain insights into model perturbations, worst-case scenarios, and training schematics. Analyze quantitative results, focusing on small structure and detail errors. Conclude with key takeaways, a discussion on the minimax problem, and the generalizability of the presented methods. This comprehensive webinar offers a deep dive into cutting-edge CT imaging techniques and their practical applications.

SPACE Webinar: X-ray CT Scatter Modeling and Estimation

IEEE Signal Processing Society
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