Application of Neural Networks in Ultrasound Computed Tomography

This work developed an image reconstruction system within the framework of Ultrasound Computed Tomography, utilizing deep learning techniques for the estimation of velocity maps associated with acoustic wave propagation. The design and training of different neural network architectures were addresse...

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Autores principales: Diaz Falvo, Malena Camila, González, Martín Germán, Rey Vega, Leonardo
Formato: Artículo publishedVersion
Lenguaje:Español
Publicado: FIUBA 2025
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Acceso en línea:https://elektron.fi.uba.ar/elektron/article/view/223
https://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=elektron&d=223_oai
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Sumario:This work developed an image reconstruction system within the framework of Ultrasound Computed Tomography, utilizing deep learning techniques for the estimation of velocity maps associated with acoustic wave propagation. The design and training of different neural network architectures were addressed, and their performance was evaluated. To this end, a synthetic dataset was generated through simulations, and the acquisition of real sinograms was performed using an experimental system that employs an immersion transducer.