Cargando…
Deep learning‐based reconstruction of in vivo pelvis conductivity with a 3D patch‐based convolutional neural network trained on simulated MR data
PURPOSE: To demonstrate that mapping pelvis conductivity at 3T with deep learning (DL) is feasible. METHODS: 210 dielectric pelvic models were generated based on CT scans of 42 cervical cancer patients. For all dielectric models, electromagnetic and MR simulations with realistic accuracy and precisi...
| Autores principales: | , , , , , , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
John Wiley and Sons Inc.
2020
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7402024/ https://www.ncbi.nlm.nih.gov/pubmed/32314825 http://dx.doi.org/10.1002/mrm.28285 |