Computed tomography (CT) reconstruction with a well-registered priori magnetic resonance imaging
(MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images
have similar structures. However, in clinical settings, the CT image of patients does not always match the priori
MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in
this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets
are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI
algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with
the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group
CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images
are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained
without using the expansion.
WANG Qihui (王齐辉), XI Yan (奚岩), CHEN Yi (陈毅),ZHANG Weikang (张伟康), ZHAO Jun* (赵俊)
. CT Reconstruction with Priori MRI Images Through Multi-Group Datasets Expansion[J]. Journal of Shanghai Jiaotong University(Science), 2017
, 22(6)
: 756
-762
.
DOI: 10.1007/s12204-017-1897-2
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