DocumentCode :
47749
Title :
Edge-Guided Dual-Modality Image Reconstruction
Author :
Yang Lu ; Jun Zhao ; Ge Wang
Author_Institution :
Mol. Imaging Bus. Unit, Shanghai United Imaging Healthcare Co. Ltd., Shanghai, China
Volume :
2
fYear :
2014
fDate :
2014
Firstpage :
1359
Lastpage :
1363
Abstract :
To utilize the synergy between computed tomography (CT) and magnetic resonance imaging (MRI) data sets from an object at the same time, an edge-guided dual-modality image reconstruction approach is proposed. The key is to establish a knowledge-based connection between these two data sets for the tight fusion of different imaging modalities. Our scheme consists of four inter-related elements: 1) segmentation; 2) initial guess generation; 3) CT image reconstruction; and 4) MRI image reconstruction. Our experiments show that, aided by the image obtained from one imaging modality, even with highly under-sampled data, we can better reconstruct the image of the other modality. This approach can be potentially useful for a simultaneous CT-MRI system.
Keywords :
biomedical MRI; computerised tomography; image fusion; image reconstruction; image segmentation; medical image processing; MRI; computed tomography; edge-guided dual-modality image reconstruction; image fusion; image segmentation; imaging modality; magnetic resonance imaging; Biomedical image processing; Computed tomography; Image processing; Image reconstruction; Magnetic resonance imaging; $l_{1}$ -norm minimization; CT-MRI system; image reconstruction; l -norm minimization; multi-modality imaging;
fLanguage :
English
Journal_Title :
Access, IEEE
Publisher :
ieee
ISSN :
2169-3536
Type :
jour
DOI :
10.1109/ACCESS.2014.2371994
Filename :
6962888
Link To Document :
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