Temperature distribution imaging in concave-shaped space from time-of-flight of acoustic wave by maximum likelihood expectation maximization algorithm
Temperature distribution imaging in concave-shaped space from time-of-flight of acoustic wave by maximum likelihood expectation maximization algorithm
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发表时间：
2010
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通讯作者：
A. Minamide;N. Wakatsuki;K. Mizutani
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作者：
A. Minamide;N. Wakatsuki;K. Mizutani
温度分布测量在各个领域都很重要。因此，人们提出了多种测量方法。在这些方法中，我们研究了利用声波飞行时间（TOF）的声学计算机断层扫描（A-CT）来测量凹形空间中的温度分布。该方法基于 Radon 逆变换，这是一种分析重建技术。然而，还澄清了这种方法很复杂并且会发生错误，因为沿着被墙壁消音的声音路径的投影数据被视为空心投影。为了解决这些问题，我们采用最大似然期望最大化（ML-EM）算法，该算法被建议用于参考文献中的 A-CT。 3. ML-EM算法是最初为正电子发射断层扫描（PET）提出的迭代重建技术之一。该算法相对于空心投影具有优势。我们部分修改算法以更适合温度分布。该算法被认为适合于凹形空间的测量。
Temperature distribution measurements are important in various fields. Thus, many kinds of measurement methods have been proposed. Among these methods, we have researched acoustic computerzed tomography (A-CT) with times of flight (TOF) of acoustic waves for the temperature distribution measurement in concave-shaped sapce. This method is based on the inverse Radon transform which is an analytical reconstruction technique. However, it has also been clarified that this method is complicated and errors occur since projection data along sound paths muffled by the wall are treated as hollow projection. To solve these problems, we employ maximum likelihood expectation maximization (ML-EM) algorithm, which is proposed to be used for A-CT in ref. 3. The ML-EM algorithm is one of the iterative reconstruction techniques originally proposed for positron emission tomography (PET). This algorithm has an advantage against the hollow projection. We partially modify the algorithm to more suit for the temperature distribution. This algorithm is considered to be suitable for the measurement in the concave-shaped space.