Structural magnetic resonance imaging (MRI) is of fundamental importance to the diagnosis
and treatment of epilepsy, particularly when surgery is being considered. Despite previous …

Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

One outstanding challenge for machine learning in diagnostic biomedical imaging is
algorithm interpretability. A key application is the identification of subtle epileptogenic focal …

Background and Objective To test the hypothesis that a multicenter-validated computer deep
learning algorithm detects MRI-negative focal cortical dysplasia (FCD). Methods We used …

Objective Drug‐resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs).
The distribution of these lesions across the cerebral cortex and the impact of lesion location …

Abstract In the recent 5 years (2014–2018), there has been growing interest in the use of
machine learning (ML) techniques to explore image diagnosis and prognosis of therapeutic …

Drug‐resistant epilepsy (DRE) considerably affects patient health, cognition, and well‐
being, and disproportionally contributes to the overall burden of epilepsy. The most common …

Objective Focal cortical dysplasia (FCD) is a major pathology in patients undergoing
surgical resection to treat pharmacoresistant epilepsy. Magnetic resonance imaging (MRI) …

Abstract Machine learning is playing an increasingly important role in medical image
analysis, spawning new advances in the clinical application of neuroimaging. There have …

Abstract Objective Focal cortical dysplasias (FCDs) are a common cause of drug‐resistant
focal epilepsy but frequently remain undetected by conventional magnetic resonance …