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Agar Gel as a Non-Invasive Coupling Medium for Reflectance Photoacoustic (PA) Imaging: Experimental Results on Wall-Painting Mock-Ups

The new reflectance set-up configuration extended the applicability of the photoacoustic (PA) imaging technique to art objects of any thickness and form. Until now, ultrasound gel or distilled water have been necessary as coupling mediums between the immersion-type transducer and the object’s surfac...

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Detalles Bibliográficos
Autores principales: Chaban, Antonina, Tserevelakis, George J., Klironomou, Evgenia, Zacharakis, Giannis, Striova, Jana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9504733/
https://www.ncbi.nlm.nih.gov/pubmed/36135400
http://dx.doi.org/10.3390/jimaging8090235
Descripción
Sumario:The new reflectance set-up configuration extended the applicability of the photoacoustic (PA) imaging technique to art objects of any thickness and form. Until now, ultrasound gel or distilled water have been necessary as coupling mediums between the immersion-type transducer and the object’s surface. These media can compromise the integrity of real artwork; therefore, known applications of reflectance PA imaging have been limited to only experimental mock-ups. In this paper, we evaluate an alternative non-invasive PA coupling medium, agar gel, applied in two layers of different consistency: first, rigid—for the protection of the object’s surface, and second, fluid—for the transducer’s immersion and movement. Agar gel is widely used in various conservation treatments on cultural heritage objects, and it has been proven to be safely applicable on delicate surfaces. Here, we quantify and compare the contrast and signal-to-noise ratio (SNR) of PA images, obtained in water and in agar gel on the same areas, at equal experimental conditions. The results demonstrate that the technique’s performance in agar is comparable to that in water. The study uncovers the advanced potential of the PA approach for revealing hidden features, and is safely applicable for future real-case studies.