{"title":"Compensating unknown speed of sound in learned fast 3D limited-view photoacoustic tomography","authors":"Jenni Poimala , Ben Cox , Andreas Hauptmann","doi":"10.1016/j.pacs.2024.100597","DOIUrl":null,"url":null,"abstract":"<div><p>Real-time applications in three-dimensional photoacoustic tomography from planar sensors rely on fast reconstruction algorithms that assume the speed of sound (SoS) in the tissue is homogeneous. Moreover, the reconstruction quality depends on the correct choice for the constant SoS. In this study, we discuss the possibility of ameliorating the problem of unknown or heterogeneous SoS distributions by using learned reconstruction methods. This can be done by modelling the uncertainties in the training data. In addition, a correction term can be included in the learned reconstruction method. We investigate the influence of both and while a learned correction component can improve reconstruction quality further, we show that a careful choice of uncertainties in the training data is the primary factor to overcome unknown SoS. We support our findings with simulated and <em>in vivo</em> measurements in 3D.</p></div>","PeriodicalId":56025,"journal":{"name":"Photoacoustics","volume":"37 ","pages":"Article 100597"},"PeriodicalIF":7.1000,"publicationDate":"2024-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2213597924000144/pdfft?md5=d4dd54258a02275b43d6bab601e52c81&pid=1-s2.0-S2213597924000144-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Photoacoustics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213597924000144","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Real-time applications in three-dimensional photoacoustic tomography from planar sensors rely on fast reconstruction algorithms that assume the speed of sound (SoS) in the tissue is homogeneous. Moreover, the reconstruction quality depends on the correct choice for the constant SoS. In this study, we discuss the possibility of ameliorating the problem of unknown or heterogeneous SoS distributions by using learned reconstruction methods. This can be done by modelling the uncertainties in the training data. In addition, a correction term can be included in the learned reconstruction method. We investigate the influence of both and while a learned correction component can improve reconstruction quality further, we show that a careful choice of uncertainties in the training data is the primary factor to overcome unknown SoS. We support our findings with simulated and in vivo measurements in 3D.
平面传感器三维光声层析成像的实时应用依赖于快速重建算法，这种算法假定组织中的声速（SoS）是均匀的。此外，重建质量取决于对恒定 SoS 的正确选择。在本研究中，我们讨论了利用学习重建方法改善未知或异质 SoS 分布问题的可能性。这可以通过对训练数据中的不确定性建模来实现。此外，还可以在学习重建方法中加入校正项。我们研究了这两种方法的影响，虽然学习到的修正项可以进一步提高重建质量，但我们发现，谨慎选择训练数据中的不确定性是克服未知 SoS 的主要因素。我们的研究结果得到了三维模拟和测量数据的支持。
PhotoacousticsPhysics and Astronomy-Atomic and Molecular Physics, and Optics
CiteScore
11.40
自引率
16.50%
发文量
96
审稿时长
53 days
期刊介绍：
The open access Photoacoustics journal (PACS) aims to publish original research and review contributions in the field of photoacoustics-optoacoustics-thermoacoustics. This field utilizes acoustical and ultrasonic phenomena excited by electromagnetic radiation for the detection, visualization, and characterization of various materials and biological tissues, including living organisms.
Recent advancements in laser technologies, ultrasound detection approaches, inverse theory, and fast reconstruction algorithms have greatly supported the rapid progress in this field. The unique contrast provided by molecular absorption in photoacoustic-optoacoustic-thermoacoustic methods has allowed for addressing unmet biological and medical needs such as pre-clinical research, clinical imaging of vasculature, tissue and disease physiology, drug efficacy, surgery guidance, and therapy monitoring.
Applications of this field encompass a wide range of medical imaging and sensing applications, including cancer, vascular diseases, brain neurophysiology, ophthalmology, and diabetes. Moreover, photoacoustics-optoacoustics-thermoacoustics is a multidisciplinary field, with contributions from chemistry and nanotechnology, where novel materials such as biodegradable nanoparticles, organic dyes, targeted agents, theranostic probes, and genetically expressed markers are being actively developed.
These advanced materials have significantly improved the signal-to-noise ratio and tissue contrast in photoacoustic methods.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
