Combined ultrasound and photoacoustic (USPA) imaging has attracted several pre-clinical and clinical applications due to its ability to simultaneously display structural, functional, and molecular information of deep biological tissue in real time. However, the depth and wavelength dependent optical attenuation and the unknown optical and acoustic heterogeneities limit the USPA imaging performance in deep tissue regions. Novel instrumentation, image reconstruction, and artificial intelligence (AI) methods are currently being investigated to overcome these limitations and improve the USPA image quality. Effective implementation of these approaches requires a reliable USPA simulation tool capable of generating US based anatomical and PA based molecular contrasts of deep biological tissue. Here, we developed a hybrid USPA simulation platform by integrating finite element models of light (NIRFast) and ultrasound (k-Wave) propagations for co-simulation of B-mode US and PA images. The platform allows optimization of different design parameters for USPA devices, such as the aperture size and frequency of both light and ultrasound detector arrays. For designing tissue-realistic digital phantoms, a dictionary-based function has been added to k-Wave to generate various levels of ultrasound speckle contrast. The feasibility of modeling US imaging combined with optical fluence dependent multispectral PA imaging is demonstrated using homogeneous as well as heterogeneous tissue phantoms mimicking human organs (e.g., prostate and finger). In addition, we also demonstrate the potential of the simulation platform to generate large scale application-specific training and test datasets for AI enhanced USPA imaging. The complete USPA simulation codes together with the supplementary user guides have been posted to an open-source repository ().

中文翻译：

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超声和光声成像组合建模：模拟辅助设备开发和人工智能

超声光声联合成像（USPA）因其能够实时同时显示深层生物组织的结构、功能和分子信息而吸引了多种临床前和临床应用。然而，深度和波长相关的光学衰减以及未知的光学和声学异质性限制了 USPA 在深层组织区域的成像性能。目前正在研究新的仪器、图像重建和人工智能 (AI) 方法，以克服这些限制并提高 USPA 图像质量。这些方法的有效实施需要可靠的 USPA 模拟工具，能够生成深层生物组织的基于 US 的解剖学和基于 PA 的分子对比。在这里，我们通过集成光 (NIRFast) 和超声 (k 波) 传播的有限元模型开发了一个混合 USPA 仿真平台，用于 B 模式 US 和 PA 图像的联合仿真。该平台可以优化 USPA 设备的不同设计参数，例如光和超声探测器阵列的孔径大小和频率。为了设计组织逼真的数字模型，k-Wave 中添加了基于字典的函数，以生成各种级别的超声散斑对比度。使用模拟人体器官（例如前列腺和手指）的同质和异质组织模型证明了超声成像与光通量依赖多光谱 PA 成像相结合建模的可行性。此外，我们还展示了模拟平台为 AI 增强型 USPA 成像生成大规模特定应用训练和测试数据集的潜力。完整的 USPA 模拟代码以及补充用户指南已发布到开源存储库 ()。