Dutta Sayantan, Mamou Jonathan
IEEE Trans Ultrason Ferroelectr Freq Control. 2025 Aug;72(8):1119-1133. doi: 10.1109/TUFFC.2025.3576239.
Quantitative acoustic microscopy (QAM) uses ultrahigh-frequency ultrasound (>200 MHz) to create 2-D maps of acoustic and mechanical properties of tissue at microscopic resolutions ( $\lt 8 ~\mu $ m). Despite significant advancements in QAM, the spatial resolution of current systems, operating at 250 and 500 MHz, may remain insufficient for certain biomedical applications. However, developing a QAM system with finer resolution by using higher-frequency transducers is costly and necessitates skilled operators, and these systems are more sensitive to the outside environment (e.g., vibrations and temperature). This study extends a resolution enhancement framework by proposing a generalized 3-D approach for processing QAM radio frequency (RF) data. The framework utilizes a quantum-based adaptive denoiser, DeQuIP, implemented as a regularization-prior (RED-prior) to enhance QAM maps. Key contributions include temporal hyperparameter optimization, accelerated algorithm integration, and application of quantum interaction theory. DeQuIP employs quantum wave functions, derived from the acquired data, as adaptive transformations that function as an RED-prior. This enables the framework to generate a temporally tailored regularization functional, allowing accurate modeling of complex physical phenomena in ultrasound propagation and providing a significant advantage over traditional regularizations in QAM imaging. The effectiveness of the proposed framework in enhancing resolution is demonstrated through both qualitative and quantitative analyses of experimental 2-D parameter maps obtained from 250- and 500-MHz QAM systems, alongside comparisons with a standard framework. Our framework demonstrates superior performance in recovering fine and subtle details, enhancing the spatial resolution of QAM maps by 38.2%-39.5%, surpassing the state-of-the-art framework, which achieved only 13.4%-26.1% improvement, and shows notable visual improvements in spatial details when compared to histology images.
定量声学显微镜（QAM）使用超高频超声（>200MHz）在微观分辨率（<8μm）下创建组织声学和力学特性的二维图。尽管QAM取得了重大进展，但目前工作在250MHz和500MHz的系统的空间分辨率对于某些生物医学应用可能仍然不足。然而，通过使用更高频率的换能器来开发具有更高分辨率的QAM系统成本高昂，并且需要熟练的操作人员，而且这些系统对外部环境（如振动和温度）更敏感。本研究通过提出一种用于处理QAM射频（RF）数据的广义三维方法，扩展了分辨率增强框架。该框架利用一种基于量子的自适应去噪器DeQuIP，作为正则化先验（RED先验）来增强QAM图。主要贡献包括时间超参数优化、加速算法集成以及量子相互作用理论的应用。DeQuIP将从采集数据中导出的量子波函数用作自适应变换，其作用类似于RED先验。这使得该框架能够生成一个时间上定制的正则化泛函，能够对超声传播中的复杂物理现象进行精确建模，并在QAM成像中提供相对于传统正则化的显著优势。通过对从250MHz和500MHz QAM系统获得的实验二维参数图进行定性和定量分析，以及与标准框架进行比较，证明了所提出框架在提高分辨率方面的有效性。我们的框架在恢复精细和细微细节方面表现出卓越性能，将QAM图的空间分辨率提高了38.2%-39.5%，超过了仅实现13.4%-26.1%改进的现有最佳框架，并且与组织学图像相比，在空间细节上显示出显著的视觉改进。
