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

In this paper, we propose a so-called AutoGate algorithm for fast and automatic Doppler gate localization in B-mode echocardiography. 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. Online clinical evaluation was performed by integrating the algorithm to a real machine. Experiment results show that the proposed algorithm performs very comparable to expert manual gate placement. To the best of our knowledge, this is the first to provide a feasible solution to automate the Doppler gate placement in real time environment.

• Type: Conference
• Year: 2008
• Where: MICCAI
• Authors: Jin Hyeong Park, Shaohua Kevin Zhou, Costas Simopoulos, Dorin Comaniciu
• Keywords: Doppler Gate Localization, Doppler Gate Placement, Gate Location Inference, Medical Imaging, MICCAI 2008