3D Radio Frequency Ultrasound Cardiac Segmentation Using a Linear Predictor [chapter]

Paul C. Pearlman, Hemant D. Tagare, Albert J. Sinusas, James S. Duncan
2010 Lecture Notes in Computer Science  
We present an approach for segmenting the left ventricular endocardial boundaries from radio-frequency (RF) ultrasound. The method employs a computationally efficient two-frame linear predictor which exploits the spatio-temporal coherence of the data. By performing segmentation using the RF data we are able to overcome problems due to image inhomogeneities that are often amplified in B-mode segmentation, as well as provide geometric constraints for RF phase-based speckle tracking. We illustrate
more » ... the advantages of our approach by comparing it to manual tracings of B-mode data and automated B-mode boundary detection using standard (Chan and Vese-based) level sets on echocardiographic images from 28 3D sequences acquired from 6 canine studies, imaged both at baseline and 1 hour post infarction.
doi:10.1007/978-3-642-15705-9_61 fatcat:qhezratadfel3hzfwtjilx7dnu