Automated segmentation of x-ray left ventricular angiograms using multi-view active appearance models and dynamic programming

Authors:
Elco Oost;Gerhard Koning;Milan Sonka;Johan H. C. Reiber;Boudewijn P. F. Lelieveldt
Affiliations:
Division of Image Processing, Department of Radiology, 1-C2S, Leiden University, Medical Center, Leiden, RC, The Netherlands;Division of Image Processing, Department of Radiology, 1-C2S, Leiden University, Medical Center, Leiden, RC, The Netherlands;Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA;Division of Image Processing, Department of Radiology, 1-C2S, Leiden University, Medical Center, Leiden, RC, The Netherlands;Division of Image Processing, Department of Radiology, 1-C2S, Leiden University, Medical Center, Leiden, RC, The Netherlands
Venue:
FIMH'05 Proceedings of the Third international conference on Functional Imaging and Modeling of the Heart
Year:
2005

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Abstract

A novel approach to automated segmentation of X-ray Left Ventricu-lar (LV) angiograms is proposed, based on Active Appearance Models (AAMs) and dynamic programming (DP). Due to combined modeling of the end-diastolic (ED) and end-systolic (ES) phase, existing correlations in shape and texture representation are exploited, resulting in a better segmentation in the ES phase. The intrinsic over-constraining by the model is compensated by a DP algorithm, in which also cardiac contraction motion features are incorporated. An elaborate evaluation of the algorithm, based on 70 paired ED-ES images, shows success rates of 100% for ED and 99% for ES, with average border positioning errors of 0.68 mm and 1.45 mm respectively. Calculated volumes were accurate and unbiased, proving the high clinical potential of our method.