Segmentation of 3D RF echocardiography using a multiframe spatio-temporal predictor.
Segmentation of 3D RF echocardiography using a multiframe spatio-temporal predictor.
复制标题
使用多帧时空预测器对 3D RF 超声心动图进行分割。
DOI：
10.1007/978-3-642-22092-0_4
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
Duncan,JamesS
中科院分区：
文献类型：
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作者：
Pearlman,PaulC;Tagare,HemantD;Lin,BenA;Sinusas,AlbertJ;Duncan,JamesS
We present an approach for segmenting left ventricular endocardial boundaries from RF ultrasound. Segmentation is achieved jointly using an independent identically distributed (i.i.d.) spatial model for RF intensity and a multiframe conditional model. The conditional model relates neighboring frames in the image sequence by means of a computationally efficient linear predictor that exploits spatio-temporal coherence in the data. Segmentation using the RF data overcomes problems due to image inhomogeneities often amplified in B-mode segmentation and provides geometric constraints for RF phase-based speckle tracking. The incorporation of multiple frames in the conditional model significantly increases the robustness and accuracy of the algorithm. Results are generated using between 2 and 5 frames of RF data for each segmentation and are validated by comparison with manual tracings and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 27 3D sequences acquired from 6 canine studies.
