AutoGate: Fast and Automatic Doppler Gate Localization in B-Mode Echocardiogram

Authors:
Jinhyeong Park;S. Kevin Zhou;Costas Simopoulos;Dorin Comaniciu
Affiliations:
Integrated Data Systems, Siemens Corporate Research, Inc., Princeton, USA;Integrated Data Systems, Siemens Corporate Research, Inc., Princeton, USA;Ultrasound Division, Siemens Medical Solution, , Mountain View, USA;Integrated Data Systems, Siemens Corporate Research, Inc., Princeton, USA
Venue:
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Year:
2008

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Abstract

In this paper, we propose an algorithm for fast and automatic Doppler gate localization in spectral Doppler echocardiography using the B-mode image information. The algorithm has two components: 1) cardiac standard view classification and 2) gate location inference. For cardiac view classification, we incorporate the probabilistic boosting network (PBN) principle to local-structure-dependent object classification, which speeds up the processing time as it breaks down the computational dependency on the number of classes. The gate location is computed using a data-driven shape inference approach. Clinical evaluation was performed by implementing the algorithm on an ultrasound system. Experiment results show that the performance of the proposed algorithm is comparable to the Doppler gate placement by an expert user. To the best of our knowledge, this is the first algorithm that provides a real time solution to the automated Doppler gate placement in the clinical environment.