Subaperture Processing-Based Adaptive Beamforming for Photoacoustic Imaging

Delay-and-sum (DAS) beamformers, when applied to photoacoustic (PA) image reconstruction, produce strong sidelobes due to the absence of transmit focusing. Consequently, DAS PA images are often severely degraded by strong off-axis clutter. For preclinical in vivo cardiac PA imaging, the presence of these noise artifacts hampers the detectability and interpretation of PA signals from the myocardial wall, crucial for studying blood-dominated cardiac pathological information and to complement functional information derived from ultrasound imaging. In this article, we present PA subaperture processing (PSAP), an adaptive beamforming method, to mitigate these image degrading effects. In PSAP, a pair of DAS reconstructed images is formed by splitting the received channel data into two complementary nonoverlapping subapertures. Then, a weighting matrix is derived by analyzing the correlation between subaperture beamformed images and multiplied with the full-aperture DAS PA image to reduce sidelobes and incoherent clutter. We validated PSAP using numerical simulation studies using point target, diffuse inclusion and microvasculature imaging, and in vivo feasibility studies on five healthy murine models. Qualitative and quantitative analysis demonstrate improvements in PAI image quality with PSAP compared to DAS and coherence factor weighted DAS (DAS CF ). PSAP demonstrated improved target detectability with a higher generalized contrast-to-noise (gCNR) ratio in vasculature simulations where PSAP produces 19.61% and 19.53% higher gCNRs than DAS and DAS CF , respectively. Furthermore, PSAP provided higher image contrast quantified using contrast ratio (CR) (e.g., PSAP produces 89.26% and 11.90% higher CR than DAS and DAS CF in vasculature simulations) and improved clutter suppression.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:68

Enthalten in:

IEEE transactions on ultrasonics, ferroelectrics, and frequency control - 68(2021), 7 vom: 01. Juli, Seite 2336-2350

Sprache:

Englisch

Beteiligte Personen:

Mukaddim, Rashid Al [VerfasserIn]
Ahmed, Rifat [VerfasserIn]
Varghese, Tomy [VerfasserIn]

Links:

Volltext

Themen:

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Anmerkungen:

Date Completed 25.10.2021

Date Revised 16.07.2022

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1109/TUFFC.2021.3060371

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM32165370X