Inverse Radon transform for optoacoustic imaging

Андреев, В. Г.; Попов, Д. А.; Sushko, D. V.; Karabutov, Alexander A.; Oraevsky, Alexander A.

doi:10.1117/12.429297

Cited by 8 publications

(4 citation statements)

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“…[10][11][12][13][14][15] Andreev et al introduced a curved, linear array for making 2D thermoacoustic images of the breast in 2000, 16 and later introduced an inverse radon transform methodology for reconstructing 2D images using such an array. 17 In this current work, we report methodology for making 2D TCT images of small animals in vivo. A unique aspect of this work is our use of a conventional, linear transducer array, which would normally be employed to acquire medical ultrasound images.…”

Section: Introductionmentioning

confidence: 99%

Thermoacoustic computed tomography using a conventional linear transducer array

et al. 2003

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We report on methodology for employing a conventional linear transducer array as a thermoacoustic detector in a thermoacoustic computed tomography (TCT) device, which has been designed for imaging small animals, e.g., athymic nude mice. We tested this concept using a 5 MHz, 128-element linear array (Acuson model L538). Thermoacoustic emissions were induced in a tissue-mimicking phantom using a Nd:YAg laser, operated at 1064 nm. Two-dimensional, axial "slice" images were formed using a filtered-backprojection algorithm. In-plane spatial resolution was measured as better than 200 microns with a slice thickness of 1.5 mm (full width at half maximum). The same detector, when operated as a conventional phased array, produced conventional ultrasound images in perfect registration with the TCT images.

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Section: Introductionmentioning

confidence: 99%

Thermoacoustic computed tomography using a conventional linear transducer array

et al. 2003

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“…A number of analytical filtered back-projection algorithms have been developed for OAT [33,[86][87][88][89][90][91][92]. The inverse problem solutions employed in these analytical algorithms have rigorous solution for complete data sets and 3D reconstruction [89]; however, back-projection algorithms yield significant artifacts and only approximate distribution of image brightness from incomplete data sets acquired using optoacoustic detector arrays with limited view.…”

Section: Algorithms Of Image Reconstructionmentioning

confidence: 99%

Near-Infrared Fluorescence Imaging and Spectroscopy in Random Media and Tissues

2014

Biomedical Photonics Handbook

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“…However, they were quickly replaced by less complex FBP algorithms and were not implemented in commercial scanners until around 10 years ago [80]. The wide use of FBP algorithms in x-ray CT fostered the development of similar formulas for OA tomography [41,42,81,82] whose discretized versions are still in common use. Particularly, GPU-based implementations of FBP algorithms enable real-time preview of three-dimensional data, which is essential for the clinical translation of the OA technology [83].…”

Section: The Inverse Problemmentioning

confidence: 99%

A practical guide for model-based reconstruction in optoacoustic imaging

Deán‐Ben

Razansky

2022

Front. Phys.

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Optoacoustic (OA, photoacoustic) imaging capitalizes on the low scattering of ultrasound within biological tissues to provide optical absorption-based contrast with high resolution at depths not reachable with optical microscopy. For deep tissue imaging applications, OA image formation commonly relies on acoustic inversion of time-resolved tomographic data. The excitation of OA responses and subsequent propagation of ultrasound waves can be mathematically described as a forward model enabling image reconstruction via algebraic inversion. These model-based reconstruction methods have been shown to outperform alternative inversion approaches and can further render OA images from incomplete datasets, strongly distorted signals or other suboptimally recorded data. Herein, we provide a general perspective on model-based OA reconstruction methods, review recent progress, and discuss the performance of the different algorithms under practical imaging scenarios.

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Inverse Radon transform for optoacoustic imaging

Cited by 8 publications

References 0 publications

Thermoacoustic computed tomography using a conventional linear transducer array

Thermoacoustic computed tomography using a conventional linear transducer array

Near-Infrared Fluorescence Imaging and Spectroscopy in Random Media and Tissues

A practical guide for model-based reconstruction in optoacoustic imaging

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