Document Detail


A new approach to contour detection in x-ray arteriograms: the wavecontour.
MedLine Citation:
PMID:  16024989     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
OBJECTIVES: We sought to develop a novel approach (the Wavecontour) for the detection of contours in vascular x-ray images, designed to eliminate any systematic underestimation or overestimation for vessel sizes in the range of 0.5 to 15 mm and further minimize the influence of the user-defined start points and end points. MATERIALS AND METHODS: This method is based on the Wavefront Propagation principle in a 2-stage approach. Two validation experiments were performed: a Plexiglas phantom study (tube sizes ranging from 0.51 to 9.9 mm) and an in vivo patient study (114 patients with various degrees of stenosis). RESULTS: The phantom study demonstrated an accuracy of 0.007 mm and a precision of 0.072 mm. The patient study showed a high similarity between the detected and the expert-drawn contours: 93% for a threshold of 1.0 pixel and 81% for a threshold of 0.5 pixels. Furthermore, the contours are robust in complex lesions and are almost independent in the middle part of the segment from the user-defined start point and end point. A variation of only 0.6 pixels exists in the middle 60% of the contours. CONCLUSIONS: Our new Wavecontour approach performs very well on phantom images as well as on clinical data over the whole range of 0.5 to 15 mm and results in more robust QCA/QVA analyses.
Authors:
Johannes P Janssen; Gerhard Koning; Patrick J H de Koning; Johan G Bosch; Joan C Tuinenburg; Johan H C Reiber
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Validation Studies    
Journal Detail:
Title:  Investigative radiology     Volume:  40     ISSN:  0020-9996     ISO Abbreviation:  Invest Radiol     Publication Date:  2005 Aug 
Date Detail:
Created Date:  2005-07-18     Completed Date:  2005-11-10     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0045377     Medline TA:  Invest Radiol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  514-20     Citation Subset:  IM    
Affiliation:
From the Department of Radiology, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, The Netherlands. J.P.Janssen@lumc.nl
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Angiography / methods*
Arterial Occlusive Diseases / radiography*
Coronary Angiography / methods
Humans
Image Processing, Computer-Assisted / methods*
Phantoms, Imaging
Reproducibility of Results

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