Real-time active shape models for segmentation of 3D cardiac ultrasound

Authors:
Jøger Hansegård;Fredrik Orderud;Stein I. Rabben
Affiliations:
University of Oslo, Norway;Norwegian University of Science and Technology, Norway;GE Vingmed Ultrasound, Norway
Venue:
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Year:
2007

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Abstract

We present a fully automatic real-time algorithm for robust and accurate left ventricular segmentation in three-dimensional (3D) cardiac ultrasound. Segmentation is performed in a sequential state estimation fashion using an extended Kalman filter to recursively predict and update the parameters of a 3D Active Shape Model (ASM) in real-time. The ASM was trained by tracing the left ventricle in 31 patients, and provided a compact and physiological realistic shape space. The feasibility of the proposed algorithm was evaluated in 21 patients, and compared to manually verified segmentations from a custom-made semi-automatic segmentation algorithm. Successful segmentation was achieved in all cases. The limits of agreement (mean±1.96SD) for the point-to-surface distance were 2.2±1.1mm. For volumes, the correlation coefficient was 0.95 and the limits of agreement were 3.4±20 ml. Real-time segmentation of 25 frames per second was achieved with a CPU load of 22%.