Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning.
Michael John James DouglassPeter GorayskiSandy PatelAlexandre SantosPublished in: Physical and engineering sciences in medicine (2023)
A deep learning model was developed, to transform 3D optical scan data of a patient into an estimated MRI volume, potentially increasing the usefulness of optical scanning in radiation therapy planning. This work has demonstrated that much of the human cranial anatomy can be predicted from the external shape of the head and may provide an additional source of valuable imaging data. Further research is required to investigate the feasibility of this approach for use in a clinical setting and further improve the model's accuracy.
Keyphrases
- high resolution
- radiation therapy
- deep learning
- contrast enhanced
- computed tomography
- high speed
- magnetic resonance imaging
- electronic health record
- endothelial cells
- big data
- artificial intelligence
- convolutional neural network
- machine learning
- diffusion weighted imaging
- radiation induced
- mass spectrometry
- case report
- magnetic resonance
- data analysis
- dual energy
- electron microscopy
- optic nerve
- optical coherence tomography