This study aims to use radiomics analysis and deep learning approaches for seizure focus detection in pediatric patients with temporal lobe epilepsy (TLE). Ten positron emission tomograph (PET) radiomics features related to pediatric temporal bole epilepsy are extracted and modelled, and the Siamese network is trained to automatically locate epileptogenic zones for assistance of diagnosis.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
The 'area under curve' (AUC ) of our model in detection performance
Timeframe: Through study completion, about 1 year