A Quantum Denoising-Based Resolution Enhancement Framework for 250-MHz and 500-MHz Quantitative Acoustic Microscopy

Abstract

Quantitative acoustic microscopy (QAM) forms two-dimensional (2D) quantitative maps of acoustic properties of thin tissue sections at a microscopic scale ( $< 8\; \mu$ m) using very-high-frequency (i.e., $>$ 200 MHz) ultrasonic excitation. Our custom-made QAM systems employ a 250-MHz or a 500-MHz single-element transducer to produce 2D maps with theoretical spatial resolutions smaller than 8 $\mu$ m and 4 $\mu$ m, respectively. Even with the utilization of these state-of-the-art QAM instruments, spatial resolution still proves insufficient for certain clinical studies. However, designing a QAM system yielding finer resolution (i.e., using a higher-frequency transducer) is expensive and requires expert users. This work proposes a scheme to enhance the spatial resolution of the 2D QAM maps by exploiting an off-the-shelf quantum-based adaptive denoiser (DeQuIP), leveraging the principles of quantum many-body theory. Drawing upon the recent advancement in regularization-by-denoising (RED) for image restoration, we impose this external DeQuIP denoiser as a RED-prior coupled with an analytical solution to address the degradation operators in solving the QAM super-resolution problem. The efficiency of our proposed scheme is demonstrated by improving the resolution of experimental 2D acoustic-impedance maps (2DZMs) generated from data acquired using the 250-MHz and 500-MHz QAM systems. Our scheme demonstrates superior performance in recovering finer and subtle details with enhanced spatial resolution when applied to 2DZMs. For example, a spatial resolution improvement of 40% was achieved when applied to 2DZMs at 250-MHz, outperforming two other state-of-the-art methods, which only yielded 23–32% improvement. These observations highlight the efficacy of the proposed RED scheme.