Generative Adversarial Network Applied to the Elimination of Noise and Artifacts in Optoacoustic Tomography Sinograms

The goal of this work is to study a preprocessing method for the data measured by a two-dimensional optoacoustic tomograph in order to reduce or eliminate artifacts introduced by the low number of detectors in the experimental setup and their limited bandwidth. A generative adversarial deep neural n...

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Detalles Bibliográficos
Autores principales: Montilla, Delfina, González, Martín German, Rey Vega, Leonardo
Formato: Artículo publishedVersion
Lenguaje:Español
Publicado: FIUBA 2023
Materias:
optoacustic tomography
machine learning
GAN
tomografía optoacústica
aprendizaje profundo
Acceso en línea:https://elektron.fi.uba.ar/elektron/article/view/180
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=elektron&d=180_oai
Aporte de:
Repositorio Digital de la Universidad de Buenos Aires (UBA) de Universidad de Buenos Aires

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