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基于理想信号逼近的内窥光声层析成像图像中声学反射伪像的抑制。

Suppression of acoustic reflection artifact in endoscopic photoacoustic tomographic images based on approximation of ideal signals.

出版信息

Technol Health Care. 2022;30(S1):201-214. doi: 10.3233/THC-228019.

DOI:10.3233/THC-228019
PMID:35124597
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9028649/
Abstract

BACKGROUND

In endoscopic photoacoustic tomography (EPAT), the photoacoustically induced ultrasonic wave reflects at tissue boundaries due to the acoustic inhomogeneity of the imaged tissue, resulting in reflection artifacts (RAs) in the reconstructed images.

OBJECTIVE

To suppress RAs in EPAT image reconstruction for improving the image quality.

METHODS

A method was presented to render the cross-sectional images of the optical absorption with reduced RAs from acoustic measurements. The ideal photoacoustic signal was recovered from acoustic signals collected by the detector through solving a least square problem. Then, high-quality images of the optical absorption distribution were reconstructed from the ideal signal.

RESULTS

The results demonstrated the improvement in the quality of the images rendered by this method in comparison with the conventional back-projection (BP) reconstructions. Compared with the short lag spatial coherence (SLSC) method, the peak signal-to-noise ratio (PSNR), normalized mean square absolute distance (NMSAD), and structural similarity (SSIM) were improved by up to 8%, 20%, and 5%, respectively.

CONCLUSIONS

This method was capable of rendering images displaying the complex tissue types with reduced RAs and lower computational burden in comparison with previously developed methods.

摘要

背景

在内窥镜光声断层扫描(EPAT)中,由于被成像组织的声特性不均匀,光声诱导的超声波在组织边界处反射,导致重建图像中出现反射伪影(RAs)。

目的

抑制 EPAT 图像重建中的 RAs,以提高图像质量。

方法

提出了一种从声学测量中减少 RAs 的方法来呈现光学吸收的横截面图像。通过求解最小二乘问题,从探测器收集的声学信号中恢复理想的光声信号。然后,从理想信号重建高质量的光学吸收分布图像。

结果

结果表明,与传统的反向投影(BP)重建相比,该方法所呈现的图像质量得到了改善。与短滞后空间相干(SLSC)方法相比,峰值信噪比(PSNR)、归一化均方绝对距离(NMSAD)和结构相似性(SSIM)分别提高了 8%、20%和 5%。

结论

与以前开发的方法相比,该方法能够呈现具有减少 RAs 和较低计算负担的复杂组织类型的图像。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/f4ad5a630aef/thc-30-thc228019-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/b82345665c49/thc-30-thc228019-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/f02b68f6e1d7/thc-30-thc228019-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/ff2640c05957/thc-30-thc228019-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/4098dff40c74/thc-30-thc228019-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/84216e69bf52/thc-30-thc228019-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/0a15d38f1e01/thc-30-thc228019-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/b02024e2c2e0/thc-30-thc228019-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/80876d1c44ac/thc-30-thc228019-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/a62a3db60849/thc-30-thc228019-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/f4ad5a630aef/thc-30-thc228019-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/b82345665c49/thc-30-thc228019-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/f02b68f6e1d7/thc-30-thc228019-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/ff2640c05957/thc-30-thc228019-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/4098dff40c74/thc-30-thc228019-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/84216e69bf52/thc-30-thc228019-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/0a15d38f1e01/thc-30-thc228019-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/b02024e2c2e0/thc-30-thc228019-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/80876d1c44ac/thc-30-thc228019-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/a62a3db60849/thc-30-thc228019-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/34dd/9028649/f4ad5a630aef/thc-30-thc228019-g010.jpg

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