ArticleAdvances in experimental medicine and biology2023
Advanced Topics in Quantitative Acoustic Microscopy.
Article in Advances in experimental medicine and biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Enhancing 3-D Radio Frequency Data in Quantitative Acoustic Microscopy Using Quantum-Driven Prior at 250 MHz and 500 MHz.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2025Article
- A Quantum Denoising-Based Resolution Enhancement Framework for 250-MHz and 500-MHz Quantitative Acoustic Microscopy.IEEE transactions on computational imaging · 2024Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative acoustic microscopy (QAM) reconstructs two-dimensional (2D) maps of the acoustic properties of thin tissue sections. Using ultrahigh frequency transducers (≥ 100 MHz), unstained, micron-thick tissue sections affixed to glass are raster scanned to collect radiofrequency (RF) echo data and generate parametric maps with resolution approximately equal to the ultrasound wavelength. 2D maps of speed of sound, mass density, acoustic impedance, bulk modulus, and acoustic attenuation provide unique and quantitative information that is complementary to typical optical microscopy modalities. Consequently, many biomedical researchers have great interest in utilizing QAM instruments to investigate the acoustic and biomechanical properties of tissues at the micron scale. Unfortunately, current state-of-the-art QAM technology is costly, requires operation by a trained user, and is accompanied by substantial experimental challenges, many of which become more onerous as the transducer frequency is increased. In this chapter, typical QAM technology and standard image formation methods are reviewed. Then, novel experimental and signal processing approaches are presented with the specific goal of reducing QAM instrument costs and improving ease of use. These methods rely on modern techniques based on compressed sensing and sparsity-based deconvolution methods. Together, these approaches could serve as the basis of the next generation of QAM instruments that are affordable and provide high-resolution QAM images with turnkey solutions requiring nearly no training to operate.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.