Title :
Lumen centerline detection in complex coronary angiograms
Author :
Sonka, Milan ; Winniford, Michael D. ; Zhang, Xiangmin ; Collins, Steve M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
fDate :
6/1/1994 12:00:00 AM
Abstract :
The authors have developed a method for lumen centerline detection in individual coronary segments that is based on simultaneous detection of the approximate positions of the left and right coronary borders. This approach emulates that of a clinician who visually identifies the lumen centerline as the midline between the simultaneously-determined left and right borders of the vessel segment of interest. The authors´ lumen centerline detection algorithm and 2 conventional centerline detection methods were compared to carefully-defined observer-identified centerlines in 89 complex coronary images. Computer-detected and observer-defined centerlines were objectively compared using 5 indices of center line position and orientation. The quality of centerlines obtained with the new simultaneous border identification approach and the 2 conventional centerline detection methods was also subjectively assessed by an experienced cardiologist who was unaware of the analysis method. The authors´ centerline detection method yielded accurate centerlines in the 89 complex images. Moreover, their method outperformed the 2 conventional methods as judged by all 5 objective parameters (p<0.001 for each parameter) and by the subjective assessment of centerline quality (p<0.001). Automated detection of lumen centerlines based on simultaneous detection of both coronary borders provides improved accuracy in complex coronary arteriograms.
Keywords :
cardiology; diagnostic radiography; medical image processing; carefully-defined observer-identified centerlines; centerline quality; complex coronary angiograms; coronary arteriograms; individual coronary segments; left coronary borders; lumen centerline detection; medical diagnostic imaging; right coronary borders; Angiography; Cardiology; Cities and towns; Density measurement; Diseases; Helium; Image reconstruction; Image segmentation; Lesions; Position measurement; Algorithms; Coronary Angiography; Coronary Disease; Evaluation Studies as Topic; Humans; Image Processing, Computer-Assisted; Observer Variation; Reproducibility of Results; Sensitivity and Specificity; Single-Blind Method;
Journal_Title :
Biomedical Engineering, IEEE Transactions on