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13 March 2017 Ultrasound elastography: efficient estimation of tissue displacement using an affine transformation model
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Ultrasound elastography entails imaging mechanical properties of tissue and is therefore of significant clinical importance. In elastography, two frames of radio-frequency (RF) ultrasound data that are obtained while the tissue is undergoing deformation, and the time-delay estimate (TDE) between the two frames is used to infer mechanical properties of tissue. TDE is a critical step in elastography, and is challenging due to noise and signal decorrelation. This paper presents a novel and robust technique TDE using all samples of RF data simultaneously. We assume tissue deformation can be approximated by an affine transformation, and hence call our method ATME (Affine Transformation Model Elastography). The affine transformation model is utilized to obtain initial estimates of axial and lateral displacement fields. The affine transformation only has six degrees of freedom (DOF), and as such, can be efficiently estimated. A nonlinear cost function that incorporates similarity of RF data intensity and prior information of displacement continuity is formulated to fine-tune the initial affine deformation field. Optimization of this function involves searching for TDE of all samples of the RF data. The optimization problem is converted to a sparse linear system of equations, which can be solved in real-time. Results on simulation are presented for validation. We further collect RF data from in-vivo patellar tendon and medial collateral ligament (MCL), and show that ATME can be used to accurately track tissue displacement.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hoda Sadat Hashemi, Mathieu Boily, Paul A. Martineau, and Hassan Rivaz "Ultrasound elastography: efficient estimation of tissue displacement using an affine transformation model", Proc. SPIE 10139, Medical Imaging 2017: Ultrasonic Imaging and Tomography, 1013903 (13 March 2017);

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