Bridge to Real Data: Empirical Multiple Material Calibration for Learning-Based Material Decomposition

Lu Y, Berger M, Manhart M, Choi JH, Hoheisel M, Kowarschik M, Fahrig R, Ren Q, Hornegger J, Maier A (2016)

Publication Type: Conference contribution

Publication year: 2016

Publisher: IEEE

Edited Volumes: Proceedings - International Symposium on Biomedical Imaging

City/Town: Prague, Czech Republic

Book Volume: 2016-June

Pages Range: 457-460

Conference Proceedings Title: Proceedings of the 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

Event location: Prague, Czech Republic

ISBN: 9781479923502

URI: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2016/Lu16-BTR.pdf

DOI: 10.1109/ISBI.2016.7493306

Abstract

In this study, we proposed an empirical multi-material calibration pipeline for learning-based material decomposition. We used realistic short scan CT data from a general metric phantom using a Siemens C-arm system, and built the corresponding numeric phantom data in a software framework. After that we applied registration approaches for matching the simulated data to the acquired data, which generates prior knowledge for the following material decomposition process, as well as the ground truth for quantitative evaluations. According to the preliminary decomposition results, we successfully decomposed the inserted phantom plugs of different materials using learning-based material decomposition process, which indicates that the proposed approach is valid for learning-based material decomposition.

Authors with CRIS profile

Involved external institutions

Stanford University United States (USA) (US) Siemens Healthineers Germany (DE) Peking University (PKU) / 北京大学 China (CN)

How to cite

APA:

Lu, Y., Berger, M., Manhart, M., Choi, J.-H., Hoheisel, M., Kowarschik, M.,... Maier, A. (2016). Bridge to Real Data: Empirical Multiple Material Calibration for Learning-Based Material Decomposition. In Proceedings of the 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro (pp. 457-460). Prague, Czech Republic: Prague, Czech Republic: IEEE.

MLA:

Lu, Yanye, et al. "Bridge to Real Data: Empirical Multiple Material Calibration for Learning-Based Material Decomposition." Proceedings of the 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic Prague, Czech Republic: IEEE, 2016. 457-460.

BibTeX: Download