Diffuse optical tomographic reconstruction using multifrequency data
Diffuse optical tomographic reconstruction using multifrequency data
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DOI：
10.1117/1.2363370
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发表时间：
2006-09-01
影响因子：
3.5
通讯作者：
Nalcioglu, Orhan
中科院分区：
文献类型：
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作者：
Unlu, Mehmet Burcin;Birgul, Ozlem;Nalcioglu, Orhan
我们研究了使用多频漫射光学层析成像（MF-DOT）数据重建光学参数。实验在一个直径为63 mm的圆柱形体中进行，其中包含一个直径为15 mm的圆柱形物体。在模体实验中，调制频率范围从110 MHz到280 MHz，在保持散射值不变的同时，改变了物体相对于模体的吸收对比度。采用有限元法求解扩散方程。每个频率的灵敏度信息被合并成一个雅可比矩阵。利用单、多调制频率数据，通过最小化测量值与正演问题之间的差值，迭代求解反问题。采用多参数Tikhonov格式进行正则化。仿真结果表明，对比背景高2.2倍的吸收对比度值和比背景高2.2倍的吸收对比度值进行双频重构，得到的目标区域的峰值吸收系数误差小于5%，对比背景高2.2倍的吸收对比度值进行双频重构，得到的峰值吸收系数误差小于10%。适当选择双频数据，与单频重建相比，双频数据的使用足以提高定量精度。(c) 2006年光学仪器工程师学会。
We investigated the use of multifrequency diffuse optical tomography (MF-DOT) data for the reconstruction of the optical parameters. The experiments were performed in a 63 mm diameter cylindrical phantom containing a 15 mm diameter cylindrical object. Modulation frequencies ranging from 110 MHz to 280 MHz were used in the phantom experiments changing the contrast in absorption of the object with respect to the phantom while keeping the scattering value the same. The diffusion equation was solved using the finite element method. The sensitivity information from each frequency was combined to form a single Jacobian. The inverse problem was solved iteratively by minimizing the difference between the measurements and forward problem using single and multiple modulation frequency data. A multiparameter Tikhonov scheme was used for regularization. The phantom results show that the peak absorption coefficient in a region of interest was obtained with an error less then 5% using two-frequency reconstruction for absorption contrast values up to 2.2 times higher than background and 10% for the absorption contrast values larger than 2.2. The use of two-frequency data is sufficient to improve the quantitative accuracy compared with the single frequency reconstruction with appropriate selection of these frequencies. (c) 2006 Society of Photo-Optical Instrumentation Engineers.