21–26 Jun 2026
U. Ottawa - Learning Crossroads (CRX) Building
America/Toronto timezone
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Quantitative Ultrasound in Synthetic Transmit Aperture Imaging

25 Jun 2026, 14:15
30m
U. Ottawa - Learning Crossroads (CRX) Building

U. Ottawa - Learning Crossroads (CRX) Building

100 Louis-Pasteur Private, Ottawa, ON K1N 9N3
Invited Speaker / Conférencier(ère) invité(e) (DPMB) R1-2 | (DPMB)

Speaker

Dr Yuan Xu (Department of Physics, Toronto Metropolitan University)

Description

Ultrasound is the most commonly used imaging modality in clinics because it is inexpensive, portable, and provides good spatial resolution with substantial penetration depth. Still, ultrasound exams often need improved contrast, and standard approaches are largely qualitative, with image quality and interpretation strongly influenced by the operator. Quantitative ultrasound (QUS), in contrast, aims to produce objective, numerical measures tied to tissue properties, which can improve diagnostic specificity.

In this work, we summarize our recent advances in reflection-mode QUS using a one-dimensional array, targeting speed-of-sound estimation, attenuation mapping, and tissue microstructure characterization. First, we derive a closed-form diffraction factor for a one-dimensional linear array, enabling reference-phantom-free QUS. Because echo intensity in a scattering medium depends on both the imaging position and probe settings, the diffraction factor is a central descriptor of the imaging system. Accounting for diffraction is critical: if left uncorrected, diffraction modifies echo amplitudes and reshapes the spectrum, introducing bias in estimates of microstructure parameters and attenuation. Although linear arrays are the most widely used transducers in clinical practice, an explicit diffraction-factor expression has been lacking; here we provide a closed-form solution for a linear rectangular array. Second, we demonstrate how this theory can be applied to attenuation imaging and tissue microstructure imaging. Finally, we introduce a new phase-aberration estimation model with potential applications to speed-of-sound imaging.

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