Conference proceeding
Feature Guided Motion Artifact Reduction with Structure-Awareness in 4D CT Images
Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.2011, pp.1057-1064
06/20/2011
DOI: 10.1109/CVPR.2011.5995561
PMCID: PMC3207360
PMID: 22058647
Abstract
In this paper, we propose a novel method to reduce the magnitude of 4D CT artifacts by stitching two images with a data-driven regularization constrain, which helps preserve the local anatomy structures. Our method first computes an interface seam for the stitching in the overlapping region of the first image, which passes through the “smoothest” region, to reduce the structure complexity along the stitching interface. Then, we compute the displacements of the seam by matching the corresponding interface seam in the second image. We use sparse 3D features as the structure cues to guide the seam matching, in which a regularization term is incorporated to keep the structure consistency. The energy function is minimized by solving a multiple-label problem in Markov Random Fields with an anatomical structure preserving regularization term. The displacements are propagated to the rest of second image and the two image are stitched along the interface seams based on the computed displacement field. The method was tested on both simulated data and clinical 4D CT images. The experiments on simulated data demonstrated that the proposed method was able to reduce the landmark distance error on average from 2.9 mm to 1.3 mm, outperforming the registration-based method by about 55%. For clinical 4D CT image data, the image quality was evaluated by three medical experts, and all identified much fewer artifacts from the resulting images by our method than from those by the compared method.
Details
- Title: Subtitle
- Feature Guided Motion Artifact Reduction with Structure-Awareness in 4D CT Images
- Creators
- Dongfeng Han - University of IowaJohn Bayouth - University of IowaQi Song - University of IowaSudershan Bhatia - University of IowaMilan Sonka - University of IowaXiaodong Wu - University of Iowa
- Resource Type
- Conference proceeding
- Publication Details
- Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol.2011, pp.1057-1064
- DOI
- 10.1109/CVPR.2011.5995561
- PMID
- 22058647
- PMCID
- PMC3207360
- NLM abbreviation
- Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
- eISBN
- 1457703939; 1457703955; 9781457703959; 9781457703935
- ISSN
- 1063-6919
- Grant note
- K25 CA123112-04 || CA / National Cancer Institute : NCI
- Language
- English
- Date published
- 06/20/2011
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; The Iowa Institute for Biomedical Imaging; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186591902771
Metrics
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