Double speed-of-sound photoacoustic image reconstruction at 10 frames-per-second with automatic segmentation

Tong Yue; Wen Jiang; Yan Luo; Hongfei Song; Xiaojun Wang; Handi Deng; Cheng Ma

doi:10.1117/12.2651263

19 December 2022 Double speed-of-sound photoacoustic image reconstruction at 10 frames-per-second with automatic segmentation

Tong Yue, Wen Jiang, Yan Luo, Hongfei Song, Xiaojun Wang, Handi Deng, Cheng Ma

Author Affiliations +

Proceedings Volume 12320, Optics in Health Care and Biomedical Optics XII; 123201D (2022) https://doi.org/10.1117/12.2651263
Event: SPIE/COS Photonics Asia, 2022, Online Only

Abstract

Photoacoustic computed tomography (PACT), also known as optoacoustic or thermoacoustic tomography, is a rapidly emerging hybrid imaging modality that combines optical image contrast with ultrasound detection. Most currently available PACT image reconstruction algorithms are based on idealized imaging models that assume a lossless and acoustically homogeneous medium. However, in many applications of PACT, if the non-uniform acoustic properties of objects are not considered in the reconstruction algorithm, the reconstructed images may contain significant distortions and artifacts. This paper proposes a fully automatic double-SoS (Speed-of-sound) reconstruction algorithm which runs at 10Hzfortwo-dimensional images of (512)(512) pixels. The algorithm uses a deep learning model to segment the animal’s outer profile from the water background. We adaptively calculate the most appropriate sound speed and assign different sound speeds to the two regions for PA image reconstruction. The reconstructed images were compared to those reconstructed using a uniform SoS quantitatively.

Conference Presentation

Citation Download Citation

Tong Yue, Wen Jiang, Yan Luo, Hongfei Song, Xiaojun Wang, Handi Deng, and Cheng Ma "Double speed-of-sound photoacoustic image reconstruction at 10 frames-per-second with automatic segmentation", Proc. SPIE 12320, Optics in Health Care and Biomedical Optics XII, 123201D (19 December 2022); https://doi.org/10.1117/12.2651263

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