arXiv subjects

Juan Aguirre

Publications and source records attributed to Juan Aguirre.

4 recordsLinked to original sources

arXiv2026

On the link between optoacoustic imaging and selective photothermolysis

Selective photothermolysis (SP) is widely used in clinical and cosmetic dermatology to remove unwanted skin structures. Careful laser parameter selection results in safe and effective target removal. Nevertheless, parameter selection relies on a trial-and-error process based on visual inspection of the immediate skin response. This process is highly dependent on the practitioner experience and can be time-consuming. SP and optoacoustic imaging (OI) share many physical principles. However, the possibility of using OI to improve laser parameter selection in SP has not been studied before. Here, we explore the relationship between OI and SP theoretically and through clinical in-human trials with a focus on tattoo removal. Our results demonstrate a strong correlation between OI signals acquired before and after treatment with the immediate clinical endpoint, suggesting that OI could be used as a tool for optimal parameter selection and reduced treatment duration in tattoo removal and other SP treatments.

physics.med-ph↗

arXiv2026

A physics inspired and efficient transform for optoacoustic systems

Optoacoustic imaging technologies require fast and accurate signal pre-processing algorithms to enable widespread deployment in clinical and home-care settings. However, they still rely on the Discrete Fourier Transform (DFT) as the default tool for essential signal-conditioning operations, which imposes hard limits on both execution speed and signal-retrieval accuracy. Here, we present a new transform whose building blocks are directly inspired by the physics of optoacoustic signal generation. We compared its performance with the DFT and other classical transforms on common signal-processing tasks using both simulations and experimental datasets. Our results indicate that the proposed transform not only sets a new lower bound on computational complexity relative to the DFT, but also substantially outperforms classical transforms on basic signal-processing operations in terms of accuracy. We expect this transform to catalyze broader adoption of optoacoustic methods.

physics.med-ph↗

arXiv2022

An image sensor based on single-pulse photoacoustic electromagnetic detection (SPEED): a simulation study

Image sensors are the backbone of many imaging technologies of great importance to modern sciences, being particularly relevant in biomedicine. An ideal image sensor should be usable through all the electromagnetic spectrum (large bandwidth), it should be fast (millions of frames per second) to fulfil the needs of many microscopy applications, and it should be cheap, in order to ensure the sustainability of the healthcare system. However, current image sensor technologies have fundamental limitations in terms of bandwidth, imaging rate or price. In here, we briefly sketch the principles of an alternative image sensor concept termed Single-pulse Photoacoustic Electromagnetic Detection (SPEED). SPEED leverages the principles of optoacoustic (photoacoustic) tomography to overcome several of the hard limitations of todays image sensors. Specifically, SPEED sensors can operate with a massive portion of the electromagnetic spectrum at high frame rate (millions of frames per second) and low cost. Using simulations, we demonstrate the feasibility of the SPEED methodology and we discuss the step towards its implementation.

physics.med-ph↗

arXiv2022

Enabling the autofocus approach for parameter optimization in planar measurement geometry clinical optoacoustic imaging

In optoacoustic (photoacoustic) tomography, several parameters related to tissue and detector features are needed for image formation, but they may not be known a priori. An autofocus (AF) algorithm is generally used to estimate these parameters. However, the algorithm works iteratively, therefore, it is impractical for clinical imaging with systems featuring planar geometry due to long reconstruction times. We have developed a fast autofocus (FAF) algorithm for optoacoustic systems with planar geometry that is much simpler computationally than the conventional AF algorithm. We show that the FAF algorithm required about 5 sec. to provide accurate estimates of the speed of sound in simulated data and experimental data obtained using an imaging system that is poised to enter the clinic. The applicability of FAF for estimating other image formation parameters is discussed. We expect the FAF algorithm to contribute decisively to the clinical use of optoacoustic tomography systems with planar geometry.

physics.med-ph↗