Amir Rosenthal1, Vasilis Ntziachristos, Daniel Razansky. 1. Institute for Biological and Medical Imaging, Technical University of Munich and Helmholtz Center Munich, 85764 Neuherberg, Germany. amir.rozental@helmholtz-muenchen.de
Abstract
PURPOSE: Optoacoustic imaging enables mapping the optical absorption of biological tissue using optical excitation and acoustic detection. Although most image-reconstruction algorithms are based on the assumption of a detector with an isotropic sensitivity, the geometry of the detector often leads to a response with spatially dependent magnitude and bandwidth. This effect may lead to attenuation or distortion in the recorded signal and, consequently, in the reconstructed image. METHODS: Herein, an accurate numerical method for simulating the spatially dependent response of an arbitrary-shape acoustic transducer is presented. The method is based on an analytical solution obtained for a two-dimensional line detector. The calculated response is incorporated in the forward model matrix of an optoacoustic imaging setup using temporal convolution, and image reconstruction is performed by inverting the matrix relation. RESULTS: The method was numerically and experimentally demonstrated in two dimensions for both flat and focused transducers and compared to the spatial-convolution method. In forward simulations, the developed method did not suffer from the numerical errors exhibited by the spatial-convolution method. In reconstruction simulations and experiments, the use of both temporal-convolution and spatial-convolution methods lead to an enhancement in resolution compared to a reconstruction with a point detector model. However, because of its higher modeling accuracy, the temporal-convolution method achieved a noise figure approximated three times lower than the spatial-convolution method. CONCLUSIONS: The demonstrated performance of the spatial-convolution method shows it is a powerful tool for reducing reconstruction artifacts originating from the detector finite size and improving the quality of optoacoustic reconstructions. Furthermore, the method may be used for assessing new system designs. Specifically, detectors with nonstandard shapes may be investigated.
PURPOSE: Optoacoustic imaging enables mapping the optical absorption of biological tissue using optical excitation and acoustic detection. Although most image-reconstruction algorithms are based on the assumption of a detector with an isotropic sensitivity, the geometry of the detector often leads to a response with spatially dependent magnitude and bandwidth. This effect may lead to attenuation or distortion in the recorded signal and, consequently, in the reconstructed image. METHODS: Herein, an accurate numerical method for simulating the spatially dependent response of an arbitrary-shape acoustic transducer is presented. The method is based on an analytical solution obtained for a two-dimensional line detector. The calculated response is incorporated in the forward model matrix of an optoacoustic imaging setup using temporal convolution, and image reconstruction is performed by inverting the matrix relation. RESULTS: The method was numerically and experimentally demonstrated in two dimensions for both flat and focused transducers and compared to the spatial-convolution method. In forward simulations, the developed method did not suffer from the numerical errors exhibited by the spatial-convolution method. In reconstruction simulations and experiments, the use of both temporal-convolution and spatial-convolution methods lead to an enhancement in resolution compared to a reconstruction with a point detector model. However, because of its higher modeling accuracy, the temporal-convolution method achieved a noise figure approximated three times lower than the spatial-convolution method. CONCLUSIONS: The demonstrated performance of the spatial-convolution method shows it is a powerful tool for reducing reconstruction artifacts originating from the detector finite size and improving the quality of optoacoustic reconstructions. Furthermore, the method may be used for assessing new system designs. Specifically, detectors with nonstandard shapes may be investigated.
Authors: Amir Rosenthal; Stephan Kellnberger; Murad Omar; Daniel Razansky; Vasilis Ntziachristos Journal: J Vis Exp Date: 2014-05-11 Impact factor: 1.355
Authors: Qiwei Sheng; Kun Wang; Thomas P Matthews; Jun Xia; Liren Zhu; Lihong V Wang; Mark A Anastasio Journal: IEEE Trans Med Imaging Date: 2015-12 Impact factor: 10.048
Authors: Lu Ding; Xose Luis Dean-Ben; Neal C Burton; Robert W Sobol; Vasilis Ntziachristos; Daniel Razansky Journal: IEEE Trans Med Imaging Date: 2017-03-22 Impact factor: 10.048