Document Detail

A three-dimensional statistical approach to improved image quality for multislice helical CT.
MedLine Citation:
PMID:  18072519     Owner:  NLM     Status:  MEDLINE    
Multislice helical computed tomography scanning offers the advantages of faster acquisition and wide organ coverage for routine clinical diagnostic purposes. However, image reconstruction is faced with the challenges of three-dimensional cone-beam geometry, data completeness issues, and low dosage. Of all available reconstruction methods, statistical iterative reconstruction (IR) techniques appear particularly promising since they provide the flexibility of accurate physical noise modeling and geometric system description. In this paper, we present the application of Bayesian iterative algorithms to real 3D multislice helical data to demonstrate significant image quality improvement over conventional techniques. We also introduce a novel prior distribution designed to provide flexibility in its parameters to fine-tune image quality. Specifically, enhanced image resolution and lower noise have been achieved, concurrently with the reduction of helical cone-beam artifacts, as demonstrated by phantom studies. Clinical results also illustrate the capabilities of the algorithm on real patient data. Although computational load remains a significant challenge for practical development, superior image quality combined with advancements in computing technology make IR techniques a legitimate candidate for future clinical applications.
Jean-Baptiste Thibault; Ken D Sauer; Charles A Bouman; Jiang Hsieh
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Medical physics     Volume:  34     ISSN:  0094-2405     ISO Abbreviation:  Med Phys     Publication Date:  2007 Nov 
Date Detail:
Created Date:  2007-12-12     Completed Date:  2008-01-03     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0425746     Medline TA:  Med Phys     Country:  United States    
Other Details:
Languages:  eng     Pagination:  4526-44     Citation Subset:  IM    
Applied Science Laboratory, GE Healthcare, 3000 N. Grandview Boulevard, W-1180, Waukesha, Wisconsin 53188, USA.
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MeSH Terms
Bayes Theorem
Brain / pathology
Computer Simulation
Equipment Design
Image Processing, Computer-Assisted / methods*
Imaging, Three-Dimensional
Models, Statistical
Models, Theoretical
Phantoms, Imaging
Radiographic Image Interpretation, Computer-Assisted / methods*
Tomography, Spiral Computed / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine

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