Univ. Grenoble Alpes, CNRS, LIPhy, 38000, Grenoble, France.
Department of Applied Physics, Hebrew University of Jerusalem, 9190401, Jerusalem, Israel.
Sci Rep. 2020 Mar 13;10(1):4637. doi: 10.1038/s41598-020-61083-2.
It has previously been demonstrated that model-based reconstruction methods relying on a priori knowledge of the imaging point spread function (PSF) coupled to sparsity priors on the object to image can provide super-resolution in photoacoustic (PA) or in ultrasound (US) imaging. Here, we experimentally show that such reconstruction also leads to super-resolution in both PA and US imaging with arrays having much less elements than used conventionally (sparse arrays). As a proof of concept, we obtained super-resolution PA and US cross-sectional images of microfluidic channels with only 8 elements of a 128-elements linear array using a reconstruction approach based on a linear propagation forward model and assuming sparsity of the imaged structure. Although the microchannels appear indistinguishable in the conventional delay-and-sum images obtained with all the 128 transducer elements, the applied sparsity-constrained model-based reconstruction provides super-resolution with down to only 8 elements. We also report simulation results showing that the minimal number of transducer elements required to obtain a correct reconstruction is fundamentally limited by the signal-to-noise ratio. The proposed method can be straigthforwardly applied to any transducer geometry, including 2D sparse arrays for 3D super-resolution PA and US imaging.
先前已经证明，基于成像点扩散函数（PSF）的先验知识并结合对物体到图像的稀疏先验的基于模型的重建方法可以在光声（PA）或超声（US）成像中提供超分辨率。在这里，我们通过实验表明，这种重建方法也可以在具有比传统方法少得多的元素的阵列（稀疏阵列）中实现 PA 和 US 成像的超分辨率。作为概念验证，我们使用基于线性传播正向模型并假设成像结构稀疏的重建方法，仅使用 128 个线性阵列的 8 个元素获得了微流控通道的超分辨率 PA 和 US 横截面图像。尽管在使用所有 128 个换能器元件获得的常规延迟和求和图像中微通道看起来无法区分，但应用的基于稀疏约束的模型重建可以在仅使用 8 个元件的情况下提供超分辨率。我们还报告了模拟结果，表明获得正确重建所需的最小换能器元件数量受到信号噪声比的根本限制。所提出的方法可以直接应用于任何换能器几何形状，包括用于 3D 超分辨率 PA 和 US 成像的 2D 稀疏阵列。
