- Evaluation of an Artificial Intelligence Model for Identification of Mass Effect and Vasogenic Edema on CT of the Head
This study compared the accuracy of a stand-alone AI model with consensus neuroradiologists’ interpretations in detecting mass effect and vasogenic edema on CT of the head. The ability to identify these findings could assist the clinical workflow through prioritizing the interpretation of abnormal cases.
- 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.
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