Paper Info
Title
Multi-atlas-based CT synthesis from conventional MRI with patch-based refinement for MRI-based radiotherapy planning.
Abstract
CT synthesis, sometimes called electron density estimation, from MRI is crucial for successful MRI-based radiotherapy planning and dose computation. Existing CT synthesis methods are able to synthesize normal tissues but are unable to accurately synthesize abnormal tissues (i.e., tumor), thus providing a suboptimal solution. We propose a multi atlas -based hybrid synthesis approach that combines multi-atlas registration and patch-based synthesis to accurately synthesize both normal and abnormal tissues. Multi-parametric atlas MR images are registered to the target MR images by multi-channel deformable registration, from which the atlas CT images are deformed and fused by locally-weighted averaging using a structural similarity measure (SSIM). Synthetic MR images are also computed from the registered atlas MRIs by using the same weights used for the CT synthesis; these are compared to the target patient MRIs allowing for the assessment of the CT synthesis fidelity. Poor synthesis regions are automatically detected based on the fidelity measure and refined by a patch-based synthesis. The proposed approach was tested on brain cancer patient data, and showed a noticeable improvement for the tumor region.
Year
DOI
Venue
2017
10.1117/12.2254571
Proceedings of SPIE
Keywords
Field
DocType
CT synthesis,multi-atlas registration,patch based synthesis,MRI-based radiotherapy planning,multichannel registration
Computer vision,Radiation therapy,Atlas (anatomy),Artificial intelligence,Image registration,Magnetic resonance imaging,Physics
Conference
Volume
ISSN
Citations 
10133
0277-786X
1
PageRank 
References 
Authors
0.37
2
5
Name
Order
Citations
PageRank
Junghoon Lee1387.21
Aaron Carass238343.15
Amod Jog317413.09
Can Zhao4234.60
Jerry L. Prince54990488.42