MRI-based Identification and Classification of Major Intracranial Tumor Types by Using a 3D Convolutional Neural Network: A Retrospective Multi-institutional Analysis.
Satrajit ChakrabartyAristeidis SotirasMikhail MilchenkoPamela LaMontagneMichael HilemanDaniel S MarcusPublished in: Radiology. Artificial intelligence (2021)
The developed model was capable of classifying postcontrast T1-weighted MRI scans of different intracranial tumor types and discriminating images depicting pathologic conditions from images depicting HLTH.Keywords MR-Imaging, CNS, Brain/Brain Stem, Diagnosis/Classification/Application Domain, Supervised Learning, Convolutional Neural Network, Deep Learning Algorithms, Machine Learning Algorithms Supplemental material is available for this article. © RSNA, 2021.
Keyphrases
- convolutional neural network
- deep learning
- machine learning
- contrast enhanced
- artificial intelligence
- magnetic resonance imaging
- computed tomography
- resting state
- magnetic resonance
- white matter
- big data
- diffusion weighted imaging
- functional connectivity
- blood brain barrier
- neoadjuvant chemotherapy
- cerebral ischemia
- squamous cell carcinoma
- lymph node
- radiation therapy
- optical coherence tomography
- subarachnoid hemorrhage