Resumen

SANCHEZ-MEDEL, Nohemí; ZETERA-DIAZ, Juan Josefat; DIAZ-HERNANDEZ, Raquel  y  ALTAMIRANO ROBLES, Leopoldo. Photoacoustic Imaging and Deep Learning in MedicalApplications. RCIM [online]. 2023, vol.15, n.2  Epub 01-Dic-2023. ISSN 1684-1859.

In recent decades, photoacoustic imaging has proven its effectiveness in supporting the diagnosis of some diseases as well as in medical research, since through them it is possible to obtain information of the human body with specific characteristics and depth of penetration, from 1 cm to 6 cm depending largely on the tissue studied, in addition to a good resolution. Photoacoustic imaging is comparatively young and emerging and promises real-time measurements, with non-invasive and radiation-free procedures. On the other hand, applying Deep Learning to photoacoustic images allows managing data and transforming them into useful information that generates knowledge. These applications have unique advantages that facilitate clinical application. It may be possible with these techniques to provide reliable medical diagnoses. That is why the aim of this article is to provide an overview of cases combining Deep Learning with photoacoustic techniques.

Palabras clave : photoacoustic imaging; deep learning; neural networks; machine learning.

        · resumen en Español     · texto en Español     · Español ( pdf )