Cargando…
A deep learning method for image‐based subject‐specific local SAR assessment
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to include this intersubject variability. In this wor...
Autores principales: | Meliadò, E.F., Raaijmakers, A.J.E, Sbrizzi, A., Steensma, B.R., Maspero, M., Savenije, M.H.F., Luijten, P.R., van den Berg, C.A.T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6899474/ https://www.ncbi.nlm.nih.gov/pubmed/31483521 http://dx.doi.org/10.1002/mrm.27948 |
Ejemplares similares
-
Conditional safety margins for less conservative peak local SAR assessment: A probabilistic approach
por: Meliadò, Ettore Flavio, et al.
Publicado: (2020) -
Real‐time assessment of potential peak local specific absorption rate value without phase monitoring: Trigonometric maximization method for worst‐case local specific absorption rate determination
por: Meliadò, Ettore Flavio, et al.
Publicado: (2020) -
Optimal control design of turbo spin‐echo sequences with applications to parallel‐transmit systems
por: Sbrizzi, Alessandro, et al.
Publicado: (2016) -
Accelerating implant RF safety assessment using a low‐rank inverse update method
por: Stijnman, Peter R. S., et al.
Publicado: (2019) -
Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k‐space data using low‐rank MR‐MOTUS
por: Huttinga, Niek R. F., et al.
Publicado: (2020)