Convolutional Neural Networks for Automatic Detection of Focal Cortical Dysplasia

Ruslan Aliev, Ekaterina Kondrateva, Maxim Sharaev, Oleg Bronov, Alexey Marinets, Sergey Subbotin, Alexander Bernstein, Evgeny Burnaev

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationAdvances in Cognitive Research, Artificial Intelligence and Neuroinformatics - Proceedings of the 9th International Conference on Cognitive Sciences, Intercognsci-2020
EditorsBoris M. Velichkovsky, Pavel M. Balaban, Vadim L. Ushakov
PublisherSpringer Science and Business Media Deutschland GmbH
Pages582-588
Number of pages7
ISBN (Print)9783030716363
DOIs
Publication statusPublished - 2021
Event9th International Conference on Cognitive Sciences, Intercognsci 2020 - Moscow, Russian Federation
Duration: 10 Oct 202016 Oct 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1358 AIST
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference9th International Conference on Cognitive Sciences, Intercognsci 2020
Country/TerritoryRussian Federation
CityMoscow
Period10/10/2016/10/20

Keywords

  • CNN
  • Computer vision
  • Deep learning
  • Epilepsy
  • FCD
  • Focal cortical dysplasia
  • Medical detection
  • MRI

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