Deep learning–based MR‐to‐CT synthesis: The influence of varying gradient echo–based MR images as input channels

PURPOSE: To study the influence of gradient echo–based contrasts as input channels to a 3D patch‐based neural network trained for synthetic CT (sCT) generation in canine and human populations. METHODS: Magnetic resonance images and CT scans of human and canine pelvic regions were acquired and paired...

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Detalles Bibliográficos
Autores principales: Florkow, Mateusz C., Zijlstra, Frank, Willemsen, Koen, Maspero, Matteo, van den Berg, Cornelis A. T., Kerkmeijer, Linda G. W., Castelein, René M., Weinans, Harrie, Viergever, Max A., van Stralen, Marijn, Seevinck, Peter R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Full Papers—Computer Processing and Modeling
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972695/
https://www.ncbi.nlm.nih.gov/pubmed/31593328
http://dx.doi.org/10.1002/mrm.28008

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6972695/
https://www.ncbi.nlm.nih.gov/pubmed/31593328
http://dx.doi.org/10.1002/mrm.28008

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