Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review.
David Jiménez-Murillo1, Andrés Eduardo Castro-Ospina1, Leonardo Duque-Muñoz1
1Grupo de investigación Máquinas Inteligentes y Reconocimiento de Patrones, Instituto Tecnológico Metropolitano, Medellín 050013, Colombia.
Sensors (Basel, Switzerland)
|August 26, 2023
Summary
Focal cortical dysplasia (FCD), a brain malformation linked to epilepsy, can be diagnosed using automated Magnetic Resonance Imaging (MRI) methods. This review explores current techniques for automatic FCD identification via MRI, aiding diagnosis and management.
Area of Science:
- Neuroimaging
- Neurology
- Medical Diagnostics
Background:
- Focal cortical dysplasia (FCD) is a congenital brain malformation frequently associated with epilepsy.
- Accurate and early diagnosis of FCD is critical for effective patient management and treatment.
- Magnetic Resonance Imaging (MRI) is a key non-invasive neuroimaging modality for evaluating brain structure and diagnosing FCD.
Approach:
- This review systematically analyzed 65 relevant papers following the PRISMA statement.
- The study categorizes FCD identification methods based on MRI into visual, semi-automatic, and fully automatic approaches.
- The focus is on evaluating the state-of-the-art in automatic FCD identification techniques using MRI.
Key Points:
- Automatic FCD identification using MRI offers a promising avenue for improving diagnostic accuracy and efficiency.
- The review highlights significant progress in automated FCD detection methods while acknowledging existing challenges.
- Future advancements include integrating automatic tools into medical imaging software and utilizing advanced MRI sequences for enhanced resolution.
Conclusions:
- This review provides a comprehensive overview of automatic FCD identification using MRI, summarizing current advancements and future directions.
- The integration of automated diagnostic tools is expected to enhance the capabilities of neurologists and radiologists.
- Continued development in MRI technology and automated analysis will further refine the precise characterization and management of FCD.
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