Title :
Self-assessing image-based respiratory motion compensation for fluoroscopic coronary roadmapping
Author :
Manhart, Michael ; Zhu, Ying ; Vitanovski, Dime
Author_Institution :
Siemens Corp. Res., Princeton, NJ, USA
fDate :
March 30 2011-April 2 2011
Abstract :
We present a self-assessing image-based motion compensation method for coronary roadmapping in fluoroscopic images. Extending our previous work on respiratory motion compensation, we introduce kernel-based nonparametric data analysis in this work to better characterize the objective function involved in motion estimation, which leads to two new improvements in motion compensation. First, through mode analysis we are able to capture the dominant component of the respiratory image motion and increase the chance of finding the global optimum. Second, an information theoretic measure is proposed to assess the uncertainty of the motion estimation and automatically detect unreliable motion estimates. The benefits of the proposed method are shown through evaluations performed on real clinical data from different procedures of percutaneous coronary interventions.
Keywords :
blood vessels; diagnostic radiography; information theory; medical image processing; motion compensation; motion estimation; pneumodynamics; fluoroscopic coronary roadmapping; information theoretic measure; kernel based nonparametric data analysis; mode analysis; motion estimation uncertainty; objective function; percutaneous coronary interventions; self assessing image based respiratory motion compensation; unreliable motion estimate detection; Approximation methods; Motion compensation; Motion estimation; Optimization; Pixel; Spline; Uncertainty; Coronary Roadmapping; Fluoroscopic Angiography; Image Guidance; Image Motion Compensation; Uncertainty Analysis;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2011 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4244-4127-3
Electronic_ISBN :
1945-7928
DOI :
10.1109/ISBI.2011.5872585