UNet and MobileNet CNN-based model observers for CT protocol optimization: comparative performance evaluation by means of phantom CT images

PURPOSE: The aim of this work is the development and characterization of a model observer (MO) based on convolutional neural networks (CNNs), trained to mimic human observers in image evaluation in terms of detection and localization of low-contrast objects in CT scans acquired on a reference phanto...

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Detalles Bibliográficos
Autores principales: Valeri, Federico, Bartolucci, Maurizio, Cantoni, Elena, Carpi, Roberto, Cisbani, Evaristo, Cupparo, Ilaria, Doria, Sandra, Gori, Cesare, Grigioni, Mauro, Lasagni, Lorenzo, Marconi, Alessandro, Mazzoni, Lorenzo Nicola, Miele, Vittorio, Pradella, Silvia, Risaliti, Guido, Sanguineti, Valentina, Sona, Diego, Vannucchi, Letizia, Taddeucci, Adriana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2023
Materias:
Special Issue on Medical Image Perception and Observer Performance
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9989681/
https://www.ncbi.nlm.nih.gov/pubmed/36895439
http://dx.doi.org/10.1117/1.JMI.10.S1.S11904

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9989681/
https://www.ncbi.nlm.nih.gov/pubmed/36895439
http://dx.doi.org/10.1117/1.JMI.10.S1.S11904

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