More articles from ARTIFICIAL INTELLIGENCE
- MR Cranial Bone Imaging: Evaluation of Both Motion-Corrected and Automated Deep Learning Pseudo-CT Estimated MR Images
In this study, the authors developed automated motion correction and used deep learning to generate pseudo-CT cranial images from MR images. Compared with CT, pseudo-CT had 100% specificity and 100% sensitivity for suture closure and 100% specificity and 90% sensitivity for skull fractures.
- Synthesizing Contrast-Enhanced MR Images from Noncontrast MR Images Using Deep Learning
The authors developed and trained a novel deep learning model utilizing a diverse multi-institutional data set that was able to synthesize virtual contrast-enhanced T1-weighted images for primary brain tumors by using only noncontrast FLAIR, T2-weighted, and T1-weighted images.