Book chapter
Motion Artifact Reduction in 4D Helical CT: Graph-Based Structure Alignment
Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, pp.63-73
Lecture Notes in Computer Science, Springer Berlin Heidelberg
2011
DOI: 10.1007/978-3-642-18421-5_7
Abstract
Four dimensional CT (4D CT) provides a way to reduce positional uncertainties caused by respiratory motion. Due to the inconsistencies of patient’s breathing, images from different respiratory periods may be misaligned, thus the acquired 3D data may not accurately represent the anatomy. In this paper, we propose a method based on graph algorithms to reduce the magnitude of artifacts present in helical 4D CT images. The method strives to reduce the magnitude of artifacts directly from the reconstructed images. The experiments on simulated data showed that the proposed method reduced the landmarks distance errors from 2.7 mm to 1.5 mm, outperforming the registration methods by about 42%. For clinical 4D CT image data, the image quality was evaluated by the three medical experts and both of who identified much fewer artifacts from the resulting images by our method than from those by the commercial 4D CT software.
Details
- Title: Subtitle
- Motion Artifact Reduction in 4D Helical CT: Graph-Based Structure Alignment
- Creators
- Dongfeng Han - University of IowaJohn Bayouth - University of IowaSudershan Bhatia - University of IowaMilan Sonka - University of IowaXiaodong Wu - University of Iowa
- Resource Type
- Book chapter
- Publication Details
- Medical Computer Vision. Recognition Techniques and Applications in Medical Imaging, pp.63-73
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-642-18421-5_7
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Publisher
- Springer Berlin Heidelberg; Berlin, Heidelberg
- Language
- English
- Date published
- 2011
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Electrical and Computer Engineering; Radiation Oncology; Fraternal Order of Eagles Diabetes Research Center; Injury Prevention Research Center; Ophthalmology and Visual Sciences
- Record Identifier
- 9984186704802771
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