Multiscale Multispectral Optoacoustic Tomography by a Stationary Wavelet Transform Prior to Unmixing
Multiscale Multispectral Optoacoustic Tomography by a Stationary Wavelet Transform Prior to Unmixing
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DOI：
10.1109/tmi.2014.2308578
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发表时间：
2014-02
影响因子：
10.6
通讯作者：
A. Taruttis;A. Rosenthal;Marcin Kacprowicz;N. Burton;V. Ntziachristos
中科院分区：
文献类型：
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作者：
A. Taruttis;A. Rosenthal;Marcin Kacprowicz;N. Burton;V. Ntziachristos
多光谱光声断层扫描（MSOT）利用宽带超声检测在一定范围内成像生物相关的光学吸收特征。由于该技术的多尺度和多光谱特性，MSOT在实施和数据分析方面有不同的要求。在这项工作中，我们研究了尺度（取决于超声波检测频率）和光学多光谱分析之间的相互作用，这两个维度是MSOT独有的，代表了以前未探索的挑战。我们表明，超声频率相关的伪影抑制多光谱特征和复杂的光谱分析。作为回应，我们采用小波分解在每尺度基础上（或每个超声频带）执行频谱解混，并展示精细尺度特征的成像，否则被低频分量隐藏。我们通过简单的模拟来解释所提出的算法，并展示了人类受试者血管成像数据的改进性能。
Multispectral optoacoustic tomography (MSOT) utilizes broadband ultrasound detection for imaging biologically-relevant optical absorption features at a range of scales. Due to the multiscale and multispectral features of the technology, MSOT comes with distinct requirements in implementation and data analysis. In this work, we investigate the interplay between scale, which depends on ultrasonic detection frequency, and optical multispectral spectral analysis, two dimensions that are unique to MSOT and represent a previously unexplored challenge. We show that ultrasound frequency-dependent artifacts suppress multispectral features and complicate spectral analysis. In response, we employ a wavelet decomposition to perform spectral unmixing on a per-scale basis (or per ultrasound frequency band) and showcase imaging of fine-scale features otherwise hidden by low frequency components. We explain the proposed algorithm by means of simple simulations and demonstrate improved performance in imaging data of blood vessels in human subjects.