Signal and Image Processing in Biomedical Photoacoustic Imaging: A Review

被引:45
|
作者
Manwar, Rayyan [1 ]
Zafar, Mohsin [2 ]
Xu, Qiuyun [2 ]
机构
[1] Univ Illinois, Richard & Loan Hill Dept Bioengn, Chicago, IL 60607 USA
[2] Wayne State Univ, Dept Biomed Engn, Detroit, MI 48201 USA
来源
OPTICS | 2021年 / 2卷 / 01期
关键词
photoacoustic; signal enhancement; image processing; SNR; deep learning; EMPIRICAL MODE DECOMPOSITION; OPTOACOUSTIC TOMOGRAPHY; RECONSTRUCTION METHOD; BLIND-DECONVOLUTION; SEGMENTATION; MICROSCOPY; NOISE; CLASSIFICATION; IDENTIFICATION; PERFORMANCE;
D O I
10.3390/opt2010001
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Photoacoustic imaging (PAI) is a powerful imaging modality that relies on the PA effect. PAI works on the principle of electromagnetic energy absorption by the exogenous contrast agents and/or endogenous molecules present in the biological tissue, consequently generating ultrasound waves. PAI combines a high optical contrast with a high acoustic spatiotemporal resolution, allowing the non-invasive visualization of absorbers in deep structures. However, due to the optical diffusion and ultrasound attenuation in heterogeneous turbid biological tissue, the quality of the PA images deteriorates. Therefore, signal and image-processing techniques are imperative in PAI to provide high-quality images with detailed structural and functional information in deep tissues. Here, we review various signal and image processing techniques that have been developed/implemented in PAI. Our goal is to highlight the importance of image computing in photoacoustic imaging.
引用
收藏
页码:1 / 24
页数:24
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