生物光声成像中声反射伪影抑制方法的研究进展

doi:10.11896/jsjkx.200800147

摘要/Abstract

摘要： 生物光声成像(Photoacoustic Imaging,PAI)是一种新型的无创复合功能成像方法。生物组织不均匀的声学特性会使超声波在组织界面处发生反射,导致重建图像中存在伪影和失真,降低图像质量和成像深度。文中综述了目前抑制PAI声反射伪影的主要方法,包括延迟相减法、基于杂波去相关理论的方法、短滞后空间相干法、基于深度学习的方法、光声引导聚焦超声法、基于超声平面波模型的方法和多波长激励的方法等,详细介绍各方法的原理,分析其优势和不足,并展望未来的研究趋势。

关键词: 生物光声成像, 声反射伪影, 声学特性不均匀, 图像重建, 杂波

Abstract: Biological photoacoustic imaging (PAI) is a newly emerged noninvasive hybrid functional imaging modality.The acoustic inhomogeneity of the imaged tissue may lead to the reflection of the photoacoustically generated ultrasound at the tissue interfaces,resulting in the reduced image quality and limited penetration depth.In this paper,main methods of reducing acoustic reflection artifacts in photoacoustic images are reviewed including delay subtraction,decorrelation of clutter,short-lag spatial cohe-rence (SLSC),deep-learning method,photoacoustic-guided focused ultrasound (PAFUSion),plane wave ultrasound model and multi-wavelength excitation.The advantages and limits of the methods are analyzed.This paper concludes with future directions of acoustic reflection artifact reduction in photoacoustic images.

Key words: Acoustic inhomogeneity, Acoustic reflection artifact, Biological photoacoustic imaging, Clutter, Image reconstruction

中图分类号:

R318

孙正, 张小雪. 生物光声成像中声反射伪影抑制方法的研究进展[J]. 计算机科学, 2021, 48(6A): 10-14. https://doi.org/10.11896/jsjkx.200800147

SUN Zheng, ZHANG Xiao-xue. Review on Methods of Reducing Acoustic Reflection Artifact in Biological Photoacoustic Imaging[J]. Computer Science, 2021, 48(6A): 10-14. https://doi.org/10.11896/jsjkx.200800147

参考文献

[1] UPPUTURI P K,PRAMANIK M.Recent advances towardspreclinical and clinical translation of photoacoustic tomography:a review[J].Journal of Biomedical Optics,2016,22(4):041006.
[2] YAO J,WANG L V.Recent progress in photoacoustic molecular imaging[J].Current Opinion in Chemical Biology,2018,45:104-112.
[3] WISSMEYER G,PLEITEZ M A,ROSENTHAL A,et al.Looking at sound:optoacoustics with all-optical ultrasound detection[J].Light:Science & Applications,2018,7:53.
[4] POUDEL J,YANG L,ANASTASIO M A.A survey of computational frameworks for solving the acoustic inverse problem in three-dimensional photoacoustic computed tomography[J].Physics in Medicine and Biology,2019,64:14TR01.
[5] YANG L,SEONYEONG P,FATIMA A,et al.Analysis of the use of unmatched backward operators in iterative image reconstruction with application to three-dimensional optoacoustic tomography[J].IEEE Transactions on Computational Imaging,2019,5(3):437-449.
[6] YE M,YUAN J.The study of selecting the optimum SOS group based on PA imaging[J].Journal of Nanjing University (Natural Sciences),2016,52(3):528-535.
[7] HELD G,PREISSER S,GÜNHAN A H,et al.Effect of irradiation distance on image contrast in epi-optoacoustic imaging of human volunteers[J].Biomedical Optics Express,2014,5(11):3765.
[8] JAEGER M,FRENZ M,SCHWEIZER D.Iterative reconstruction algorithm for reduction of echo background in optoacoustic images[C]//Proceedings of SPIE International Conference on Photons Plus Ultrasound:Imaging and Sensing 2008.San Francisco,2008,6856:68561C.
[9] KANE S C,KHONG S L,DA SILVA COSTA F.Diagnosticimaging:ultrasound[J].Methods in Molecular Biology,2018,1710:1-8.
[10] LI W.Research on ultrasonic signal acquisition and preproces-sing in photoacoustic imaging[D].Shanghai:Fudan University,2012.
[11] ERPELDING T N,KE H,WANG L.In-place clutter reduction for photoacoustic imaging:WO2014076674A2[P].WIPO Patent,2014.
[12] JAEGER M,SIEGENTHALER L,KITZ M,et al.Reduction of background in optoacoustic image sequences obtained under tissue deformation[J].Journal of Biomedical Optics,2009,14(5):054011.
[13] JAEGER M,HARRIS-BIRTILL D,GERTSCH A,et al.De-formation compensated averaging for clutter reduction in epiphotoacoustic imaging in vivo[J].Journal of Biomedical Optics,2012,17(6):066007.
[14] JAEGER M,BAMBER J C,FRENZ M.Clutter elimination for deep clinical optoacoustic imaging using localised vibration tagging (LOVIT)[J].Photoacoustics,2013,1(2):19-29.
[15] PETROSYAN T,THEODOROU M,BAMBER J,et al.Rapid scanning wide-field clutter elimination in epi-optoacoustic imaging using comb LOVIT[J].Photoacoustics,2018,10:20-30.
[16] POUREBRAHIMI B,YOON S,KOLIOS M C.Improving thequality of photoacoustic images using the short-lag spatial coherence imaging technique[C]//Proceedings of SPIE International Conference on Photons Plus Ultrasound:Imaging and Sensing 2013.San Francisco:SPIE,2013,85813:85813Y.
[17] ALLES E J,JAEGER M,BAMBER J C.Photoacoustic clutter reduction using short-lag spatial coherence weighted imaging[C]//Proceedings of 2014 IEEE International Ultrasonics Sympo-sium.Chicago,IL,USA,2014.
[18] LEDIJU BELL M A,KUO N,SONG D Y,et al.Short-lag spatial coherence beamforming of photoacoustic images for enhanced visualization of prostate brachytherapy seeds[J].Biomedical Optics Express,2013,4(10):1964.
[19] ALLMAN D,REITER A,BELL M.Photoacoustic source detection and reflection artifact removal enabled by deep learning[J].IEEE Transactions on Medical Imaging,2018,37(6):1464-1477.
[20] ALLMAN D,REITER A,BELL M.A machine learning method to identify and remove reflection artifacts in photoacoustic channel data[C]//Proceedings of the 2017 IEEE International Ultrasonics Symposium(IUS).Washington,DC,USA,Sep.6-9,2017.
[21] ALLMAN D,REITER A.Exploring the effects of transducer models when training convolutional neural networks to eliminate reflection artifacts in experimental photoacoustic images[C]//Proceedings of SPIE International Conference on Photons Plus Ultrasound:Imaging and Sensing 2018.San Francisco,USA,2018,10494:104945H.
[22] SINGH M K A,STEENBERGEN W.Photoacoustic-guided focused ultrasound (PAFUSion) for identifying reflection artifacts in photoacoustic imaging[J].Photoacoustics,2015,3(4):123-131.
[23] SINGH M K A,JAEGER M,FRENZ M,et al.In vivo demonstration of reflection artifact reduction in photoacoustic imaging using synthetic aperture photoacoustic-guided focused ultrasound (PAFUSion)[J].Biomedical Optics Express,2016,7(8):2955-2972.
[24] SINGH M K A,PARAMESHWARAPPA V,HENDRIKSEN E,et al.Photoacoustic-guided focused ultrasound for accurate visualization of brachytherapy seeds with the photoacoustic needle[J].Journal of Biomedical Optics,2016,21(12):120501.
[25] SINGH M K A,JAEGER M,FRENZ M,et al.Reflection-artifact-free photoacoustic imaging using PAFUSion (photoacoustic-guided focused ultrasound)[C]//Proceedings of SPIE International Conference on Photons Plus Ultrasound:Imaging and Sensing 2016.San Francisco,SPIE,2016,97081:97081R.
[26] SINGH M K A,JAEGER M,FRENZ M,et al.Photoacoustic reflection artifact reduction using photoacoustic-guided focused ultrasound:comparison between plane-wave and element-by-element synthetic backpropagation approach[J].Biomedical Optics Express,2017,8(4):2245-2260.
[27] SCHWAB H M,BECKMANN M F,SCHMITZ G.Photoacoustic clutter reduction using plane wave ultrasound and a linear scatter estimation approach[C]//Proceedings of 2015 IEEE International Ultrasonics Symposium.Taipei,Taiwan,2015:21-24.
[28] SCHWAB H M,BECKMANN M F,SCHMITZ G.Photoacoustic clutter reduction by inversion of a linear scatter model using plane wave ultrasound measurements[J].Biomedical Optics Express,2016,7(4):1468-1478.
[29] SCHWAB H M,SCHMITZ G.An advanced interpolation ap-proach for photoacoustic clutter reduction based on a linear plane wave scatter model[C]//Proceedings of 2016 IEEE International Ultrasonics Symposium.Tours,France,2016:18-21.
[30] NGUYEN H N Y,HUSSAIN A,STEENBERGEN W.Reflection artifact identification in photoacoustic imaging using multi-wavelength excitation[J].Biomedical Optics Express,2018,9(10):4613-4630.

相关文章 13

[1]	孙正, 王新宇. 深度学习在光声成像中的应用现状 Application of Deep Learning in Photoacoustic Imaging 计算机科学, 2020, 47(6A): 148-152. https://doi.org/10.11896/JsJkx.190700046
[2]	温健阳,宫宁生,陈岩. 基于压缩感知的图像盲水印算法 Blind Image Watermark Algorithm Based on Compressed Sensing 计算机科学, 2016, 43(Z11): 377-382. https://doi.org/10.11896/j.issn.1002-137X.2016.11A.087
[3]	刘亚男,杨晓梅,陈超楠. 基于分数阶全变分正则化的超分辨率图像重建 Super-resolution Image Reconstruction Based on Fractional Order Total Variation Regularization 计算机科学, 2016, 43(5): 274-278. https://doi.org/10.11896/j.issn.1002-137X.2016.05.052
[4]	余沙,陈明燕,曹建蜀. 基于网格聚类和修正逻辑的航迹起始算法 Tracking Initiation Algorithm Based on Grid Clustering and Modified Logic Algorithm 计算机科学, 2015, 42(4): 181-184. https://doi.org/10.11896/j.issn.1002-137X.2015.04.036
[5]	骆岩红. CT图像重建滤波反投影算法中指数滤波器的研究 Study on Exponential Filter of Filter Back Projection Algorithm for CT Image Reconstruction 计算机科学, 2014, 41(Z6): 220-223.
[6]	朱立新,杨扩,秦加合. 一种新的基于自适应神经网络模糊推理系统的图像滤波器 New Noise Digital Images Filter Based on Adaptive Neuro-fuzzy Inference System 计算机科学, 2014, 41(Z6): 211-214.
[7]	成丽君,张宇波,徐从富. 基于混合图像分割与梯度算法的发光物体图像重建技术研究 Image Reconstruction Algorithm Based on Graph Cuts and Gradient-based Algorithms 计算机科学, 2014, 41(4): 314-318.
[8]	张顺利,张定华,李小林,刘敏娜. 基于Shepp-Logan头模型的锥束CT仿真投影快速计算 Fast Calculation of Simulation Projection for Cone-beam CT Based on Shepp-Logan Head Phantom 计算机科学, 2012, 39(5): 257-260.
[9]	张顺利，张定华，程云勇，张小波. 基于像素模型的CT仿真投影快速计算 Fast Calculation of CT Simulation Projection Based on Pixel Phantom 计算机科学, 2011, 38(7): 290-293.
[10]	张彦俊，陈宇，陈德运，于晓洋. 电阻层析成像系统敏感场特性分析及图像重建 Analyze of Sensitivity Field Characteristics and Image Reconstruction for Electrical Resistance Tomography System 计算机科学, 2010, 37(8): 257-261.
[11]	张顺利,张定华,李明君,郭新明. 基于最小圆柱区域的锥束CT快速图像重建 Fast Image Reconstruction for Cone-beam CT Based on Minimal Cylindrical Reconstruction Region 计算机科学, 2010, 37(5): 257-260.
[12]	黄华李俊齐春朱世华. 基于通用高斯马尔可夫随机场模型的图像超分辨率重建计算机科学, 2005, 32(11): 195-197.
[13]	李耀东崔霞肖柏华戴汝为. 自动人脸识别技术综述计算机科学, 2002, 29(12): 1-11.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed