A frequency-domain model-based reconstruction method for transcranial photoacoustic imaging: A 2D numerical investigation.
A frequency-domain model-based reconstruction method for transcranial photoacoustic imaging: A 2D numerical investigation.
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DOI：
10.1016/j.pacs.2023.100561
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发表时间：
2023-10
期刊：
影响因子：
7.9
通讯作者：
Jing, Yun
中科院分区：
文献类型：
--
作者：
Park, Hyungjoo;Yao, Junjie;Jing, Yun
由颅骨引起的相位像差是实现人类和非人类灵长类动物大脑高质量光声图像的主要障碍。为了解决这个问题，已经使用了时间反转方法，但由于依赖于求解全波方程，它们的计算要求很高，速度很慢。该方法基于基于模型的频域图像重建，实现近实时图像重建。成像区域与换能器阵列元素之间的关系可以用模型矩阵进行数学描述，通过模型矩阵的伪逆进行图像重建。由于缺乏经颅超声的解析解，模型矩阵采用数值计算。然而，对于给定的实验设置和相同的声学介质，该计算只需要执行一次，并且是一个离线过程，不影响实际图像重建时间。这种基于非迭代模型的方法在图像重建时间上有了实质性的改进，比时间反转方法快了大约18倍，同时保持了相当的图像质量。
Phase aberration caused by the skull is a major barrier to achieving high quality photoacoustic images of human and non-human primates’ brains. To address this issue, time-reversal methods have been used but they are computationally demanding and slow due to relying on solving the full-wave equation. The proposed approach is based on model-based image reconstruction in the frequency-domain to achieve near real-time image reconstruction. The relationship between an imaging region and transducer array elements can be mathematically described as a model matrix and the image reconstruction can be performed by pseudo-inverse of the model matrix. The model matrix is numerically calculated due to the lack of analytical solutions for transcranial ultrasound. However, this calculation only needs to be performed once for a given experimental setup and the same acoustic medium, and is an offline process not affecting the actual image reconstruction time. This non-iterative mode-based method demonstrates a substantial improvement in image reconstruction time, being approximately 18 times faster than the time-reversal method, all while maintaining comparable image quality.
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影响因子：
3.4
作者：
Hill ER;Xia W;Clarkson MJ;Desjardins AE
通讯作者：
Desjardins AE
DOI：
10.3389/fnene.2010.00010
发表时间：
2010
期刊：
Frontiers in neuroenergetics
影响因子：
--
作者：
Hu S;Wang LV
通讯作者：
Wang LV
影响因子：
10.2
作者：
HANSEN, PC
通讯作者：
HANSEN, PC
影响因子：
10.6
作者：
Ding, Lu;Dean-Ben, Xose Luis;Razansky, Daniel
通讯作者：
Razansky, Daniel
影响因子：
2.6
作者：
Glover, Gary H.
通讯作者：
Glover, Gary H.