  Focal cortical dysplasia (FCD) is one of the most common epileptogenic
lesions associated with cortical development malformations. However, the
accurate detection of the FCD relies on the radiologist professionalism, and in
many cases, the lesion could be missed. In this work, we solve the problem of
automatic identification of FCD on magnetic resonance images (MRI). For this
task, we improve recent methods of Deep Learning-based FCD detection and apply
it for a dataset of 15 labeled FCD patients. The model results in the
successful detection of FCD on 11 out of 15 subjects.
