Garcia, L and Fromageau, J and Housden, RJ and Treece, GM and Uff, C and Bamber, JC (2011) Retaining axial-lateral orthogonality in steered ultrasound data to improve image quality in reconstructed lateral displacement data. Progress in Biomedical Optics and Imaging - Proceedings of SPIE, 7961. ISSN 1605-7422Full text not available from this repository.
Ultrasound elastography tracks tissue displacements under small levels of compression to obtain images of strain, a mechanical property useful in the detection and characterization of pathology. Due to the nature of ultrasound beamforming, only tissue displacements in the direction of beam propagation, referred to as 'axial', are measured to high quality, although an ability to measure other components of tissue displacement is desired to more fully characterize the mechanical behavior of tissue. Previous studies have used multiple one-dimensional (1D) angled axial displacements tracked from steered ultrasound beams to reconstruct improved quality trans-axial displacements within the scan plane ('lateral'). We show that two-dimensional (2D) displacement tracking is not possible with unmodified electronically-steered ultrasound data, and present a method of reshaping frames of steered ultrasound data to retain axial-lateral orthogonality, which permits 2D displacement tracking. Simulated and experimental ultrasound data are used to compare changes in image quality of lateral displacements reconstructed using 1D and 2D tracked steered axial and steered lateral data. Reconstructed lateral displacement image quality generally improves with the use of 2D displacement tracking at each steering angle, relative to axial tracking alone, particularly at high levels of compression. Due to the influence of tracking noise, unsteered lateral displacements exhibit greater accuracy than axial-based reconstructions at high levels of applied strain. © 2011 SPIE.
|Uncontrolled Keywords:||beam steering Elastography lateral stiffness strain tensors ultrasound vector reconstruction|
|Divisions:||Div F > Machine Intelligence|
|Depositing User:||Cron Job|
|Date Deposited:||07 Mar 2014 12:15|
|Last Modified:||27 Nov 2014 19:19|