ArticleScientific data2023
An open presurgery MRI dataset of people with epilepsy and focal cortical dysplasia type II.
Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 42 citations in OpenAlex.
- Volume-inflation registration (INFREG) for morphometric analysis of human focal cortical dysplasia type II.iScience · 2026Article
- Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI.Research square · 2026Article
- Quantifying extra-lesional interhemispheric cortical asymmetry in focal cortical dysplasia type II.Epilepsia open · 2026Article
- Characterizing Onset Limit and Surgical Outcome Factors in Type II Focal Cortical Dysplasia-Related Epilepsy.Neurology. Clinical practice · 2026Article
- A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning.Scientific data · 2026Article
- Open diffusion magnetic resonance imaging and connectivity data for epilepsy and surgery: The IDEAS II release.Epilepsia · 2026Article
- Diagnosis of Multiple Sclerosis Using Multimodal Deep Learning Integrating Lesion and Normal-Appearing White Matter: A Retrospective Study with International Multicentre External Validation.medRxiv : the preprint server for health sciences · 2026Article
- A deep representation learning model to predict response to vagus nerve stimulation.Nature communications · 2026Article
- Pipeline evaluation of a state-of-the-art AI algorithm for detection of focal cortical dysplasia: insights into potential failure sources.Brain informatics · 2026Article
- AI in epilepsy neuroimaging.Current opinion in neurology · 2026Review
- Pseudo-healthy image synthesis via location-guided diffusion models for focal cortical dysplasia lesion localization.Scientific reports · 2026Article
- Multimodal artificial intelligence in epilepsy: antiseizure medication response, epileptogenic zone localization, and surgical outcome prediction.Frontiers in neurology · 2026Review
- A public benchmark for human performance in the detection of focal cortical dysplasia.Epilepsia open · 2025Article
- Detection of focal cortical dysplasia: Development and multicentric evaluation of artificial intelligence models.Epilepsia · 2025Article
- A new perspective on drug-resistant epilepsy in children with focal cortical dysplasia type 1: From challenge to favorable outcome.Epilepsia · 2025Article
- Cortical and subcortical morphometric changes in patients with frontal focal cortical dysplasia type II.Neuroradiology · 2025Article
- The Imaging Database for Epilepsy And Surgery (IDEAS).Epilepsia · 2025Article
- A nnU-Net-based automatic segmentation of FCD type II lesions in 3D FLAIR MRI images.Frontiers in artificial intelligence · 2025Article
- LEM-UNet: an edge-guided network for 3D multimodal images segmentation in focal cortical dysplasia.Frontiers in neuroscience · 2025Article
- Lesion distribution and network mapping in dyskinetic cerebral palsy.Brain communications · 2025Article
Corrections and comments
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Authors and funding
24 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Automated detection of lesions using artificial intelligence creates new standards in medical imaging. For people with epilepsy, automated detection of focal cortical dysplasias (FCDs) is widely used because subtle FCDs often escape conventional neuroradiological diagnosis. Accurate recognition of FCDs, however, is of outstanding importance for affected people, as surgical resection of the dysplastic cortex is associated with a high chance of postsurgical seizure freedom. Here, we make publicly available a dataset of 85 people affected by epilepsy due to FCD type II and 85 healthy control persons. We publish 3D-T1 and 3D-FLAIR, manually labeled regions of interest, and carefully selected clinical features. The open presurgery MRI dataset may be used to validate existing automated algorithms of FCD detection as well as to create new approaches. Most importantly, it will enable comparability of already existing approaches and support a more widespread use of automated lesion detection tools.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.