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Author Zhang, Yu ♦ Wu, Guorong ♦ Yap, Pew-Thian ♦ Feng, Qianjin ♦ Lian, Jun ♦ Chen, Wufan ♦ Shen, Dinggang
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Super-resolution Patch ♦ Corresponding Patch ♦ Lung Cancer Treatment ♦ Super-resolution Lung ♦ Super-resolution Axial Slice ♦ Important Role ♦ Possible Patch Location ♦ Misleading Artifact ♦ Partial Volume ♦ Guided Reconstruction ♦ Super-resolution Enhancement ♦ Patch-based Sparse Representation ♦ Particular Phase ♦ Neighboring Slice ♦ 4d-ct Sequence ♦ Sparse Combination ♦ 4d-ct Play ♦ Enhanced Anatomical Detail ♦ Lung Vessel Discontinuity ♦ Targeted Super-resolution Slice ♦ Superresolution 4d-ct Image Sequence ♦ Public Dataset ♦ Image Detail ♦ Dose Administration ♦ 4d-ct Image ♦ Radiation Therapy ♦ Cubic-spline Interpolation Method ♦ Anatomical Information ♦ Ct Image ♦ Superior-inferior Direction ♦ Novel Patch-based Technique ♦ Patch-based Mechanism ♦ Inherent High-dose Exposure
Description 4D-CT plays an important role in lung cancer treatment. However, due to the inherent high-dose exposure associated with CT, dense sampling along superior-inferior direction is often not practical. As a result, artifacts such as lung vessel discontinuity and partial volume are typical in 4D-CT images and might mislead dose administration in radiation therapy. In this paper, we present a novel patch-based technique for super-resolution enhancement of the 4D-CT images along the superior-inferior direction. Our working premise is that the anatomical information that is missing at one particular phase can be recovered from other phases. Based on this assumption, we employ a patch-based mechanism for guided reconstruction of super-resolution axial slices. Specifically, to reconstruct each targeted super-resolution slice for a CT image at a particular phase, we agglomerate a dictionary of patches from images of all other phases in the 4D-CT sequence. Then we perform a sparse combination of the patches in this dictionary to reconstruct details of a super-resolution patch, under constraint of similarity to the corresponding patches in the neighboring slices. By iterating this procedure over all possible patch locations, a superresolution 4D-CT image sequence with enhanced anatomical details can be eventually reconstructed. Our method was extensively evaluated using a public dataset. In all experiments, our method outperforms the conventional linear and cubic-spline interpolation methods in terms of preserving image details and suppressing misleading artifacts. 1.
in Proc. IEEE Conf. Comput. Vis. Pattern Recognit
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2012-01-01