Cross-sectional photoacoustic tomography image reconstruction with a multi-curve integration model.

Abstract:

BACKGROUND AND OBJECTIVE:In acoustic inversion of photoacoustic tomography (PAT), an imaging model that precisely describes both the ultrasonic wave propagation and the detector properties is of crucial importance. Inspired by the multi-stripe integration model in clinical X-ray computed tomography systems, in this work, we introduce the Multi-Curve-Integration-based acoustic inversion for cross-sectional Photoacoustic Tomography (MCI-PAT). METHODS:We assumed that in cross-sectional PAT system, the three-dimensional (3-D) wave propagation problem could be reduced to a two-dimensional (2-D) problem in a limited, yet sufficient field of view. Under such condition, the MCI-PAT imaging model is generated by integrating several circular acoustic curves, the centers of which are points evenly distributed on the finite-size ultrasonic transducer surface. In this way, the spatial detector response is taken into account, while its computational burden does not largely increase because the integration process is performed only on a 2-D plane. RESULTS:As proven by simulation, phantom and in vivo small animal experiments, the MCI-PAT method leads to promising improvement in PAT image quality. Comparing to traditional imaging models that considered only a single acoustic curve, our proposed method successfully improved the visibility of small structures and achieved evident enhancement on signal-to-noise ratio. CONCLUSIONS:The performance of the MCI-PAT method demonstrates that for cross-sectional PAT, a 2-D simplification of the propagation of multiple photoacoustic waves is feasible. Due to its simplicity, our method can be used as an add-on to current system models considering only a single acoustic curve.

authors

Qi L,Huang S,Li X,Zhang S,Lu L,Feng Q,Chen W

doi

10.1016/j.cmpb.2020.105731

subject

Has Abstract

pub_date

2020-12-01 00:00:00

pages

105731

eissn

0169-2607

issn

1872-7565

pii

S0169-2607(20)31564-9

journal_volume

197

pub_type

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