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Proceedings Paper

Unified dual-modality image reconstruction with dual dictionaries
Author(s): Yang Lu; Jun Zhao; Tiange Zhuang; Ge Wang
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Paper Abstract

To utilize the synergy between CT and MR datasets from an object at the same time, a unified dual-modality image reconstruction approach is proposed using a dual-dictionary learning technique. The key is to establish a knowledgebased connection between these two datasets for a tight fusion of different imaging modalities. Our scheme consists of three inter-related elements: dual-dictionary learning, CT image reconstruction, and MR image reconstruction. Our experiments show that even with highly under-sampled MR data and few x-ray projections, we can still satisfactorily reconstruct both MR and CT images. This approach can be potentially useful for a CT-MRI system.

Paper Details

Date Published: 17 October 2012
PDF: 7 pages
Proc. SPIE 8506, Developments in X-Ray Tomography VIII, 85061V (17 October 2012); doi: 10.1117/12.932246
Show Author Affiliations
Yang Lu, Shanghai Jiao Tong Univ. (China)
Jun Zhao, Shanghai Jiao Tong Univ. (China)
Tiange Zhuang, Shanghai Jiao Tong Univ. (China)
Ge Wang, Virginia Polytechnic Institute and State Univ. (United States)


Published in SPIE Proceedings Vol. 8506:
Developments in X-Ray Tomography VIII
Stuart R. Stock, Editor(s)

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