Comparison of Supervised and Unsupervised Approaches for the Generation of Synthetic CT from Cone-Beam CT

Due to major artifacts and uncalibrated Hounsfield units (HU), cone-beam computed tomography (CBCT) cannot be used readily for diagnostics and therapy planning purposes. This study addresses image-to-image translation by convolutional neural networks (CNNs) to convert CBCT to CT-like scans, comparin...

Descripción completa

Detalles Bibliográficos
Autores principales: Rossi, Matteo, Cerveri, Pietro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395013/
https://www.ncbi.nlm.nih.gov/pubmed/34441369
http://dx.doi.org/10.3390/diagnostics11081435

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8395013/
https://www.ncbi.nlm.nih.gov/pubmed/34441369
http://dx.doi.org/10.3390/diagnostics11081435

Ejemplares similares