Automated detection of hippocampal sclerosis using clinically empirical and radiomics features.
Jia-Jie MoZhenyu LiuKai SunYanshan MaWenhan HuChao ZhangYao WangXiu WangChang LiuBaotian ZhaoKai ZhangJian-Guo ZhangZhenyu ZhangPublished in: Epilepsia (2019)
Machine learning with quantitative clinical and radiomics features is shown to improve HS detection. HS-related structural alterations were similar in the MRI-positive and MRI-negative HS patient groups, indicating that misdiagnosis originates mainly from empirical interpretation. The cortical folding complexity of the temporal pole is a potentially valuable feature for exploring the nature of HS.
Keyphrases
- machine learning
- contrast enhanced
- magnetic resonance imaging
- deep learning
- loop mediated isothermal amplification
- lymph node metastasis
- diffusion weighted imaging
- label free
- real time pcr
- computed tomography
- artificial intelligence
- case report
- high resolution
- high throughput
- single molecule
- squamous cell carcinoma
- brain injury
- drug induced