Artificial intelligence for the detection of focal cortical dysplasia: Challenges in translating algorithms into clinical practice

L Walger, S Adler, K Wagstyl, L Henschel, B David… - …, 2023 - Wiley Online Library
Focal cortical dysplasias (FCDs) are malformations of cortical development and one of the
most common pathologies causing pharmacoresistant focal epilepsy. Resective …

Interpretable surface-based detection of focal cortical dysplasias: a Multi-centre Epilepsy Lesion Detection study

H Spitzer, M Ripart, K Whitaker, F D'Arco, K Mankad… - Brain, 2022 - academic.oup.com
One outstanding challenge for machine learning in diagnostic biomedical imaging is
algorithm interpretability. A key application is the identification of subtle epileptogenic focal …

Whole-brain morphological alterations associated with trigeminal neuralgia

J Mo, J Zhang, W Hu, F Luo, K Zhang - The journal of headache and pain, 2021 - Springer
Background Novel neuroimaging strategies have the potential to offer new insights into the
mechanistic basis for trigeminal neuralgia (TN). The present study aims to conduct whole …

External validation of automated focal cortical dysplasia detection using morphometric analysis

B David, J Kröll‐Seger, F Schuch, J Wagner… - …, 2021 - Wiley Online Library
Abstract Objective Focal cortical dysplasias (FCDs) are a common cause of drug‐resistant
focal epilepsy but frequently remain undetected by conventional magnetic resonance …

Deep learning model for the automated detection and histopathological prediction of meningioma

H Zhang, J Mo, H Jiang, Z Li, W Hu, C Zhang, Y Wang… - Neuroinformatics, 2021 - Springer
The volumetric assessment and accurate grading of meningiomas before surgery are highly
relevant for therapy planning and prognosis prediction. This study was to design a deep …

The clinical, imaging, pathological and genetic landscape of bottom-of-sulcus dysplasia

E Macdonald-Laurs, AEL Warren, P Francis… - Brain, 2024 - academic.oup.com
Bottom-of-sulcus dysplasia (BOSD) is increasingly recognized as a cause of drug-resistant,
surgically-remediable, focal epilepsy, often in seemingly MRI-negative patients. We describe …

Segmentation of focal cortical dysplasia lesions from magnetic resonance images using 3D convolutional neural networks

S Niyas, SC Vaisali, I Show, TG Chandrika… - … Signal Processing and …, 2021 - Elsevier
Computer-aided diagnosis using advanced Artific ial Intelligence (AI) techniques has
become much popular over the last few years. This work automates the segmentation of …

DeepEZ: a graph convolutional network for automated epileptogenic zone localization from resting-state fMRI connectivity

N Nandakumar, D Hsu, R Ahmed… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Objective: Epileptogenic zone (EZ) localization is a crucial step during diagnostic work up
and therapeutic planning in medication refractory epilepsy. In this paper, we present the first …

Detecting cortical thickness changes in epileptogenic lesions using machine learning

S Azzony, K Moria, J Alghamdi - Brain Sciences, 2023 - mdpi.com
Epilepsy is a neurological disorder characterized by abnormal brain activity. Epileptic
patients suffer from unpredictable seizures, which may cause a loss of awareness. Seizures …

Sulcus-centered resection for focal cortical dysplasia type II: surgical techniques and outcomes

B Zhao, C Zhang, X Wang, Y Wang, C Liu, J Mo… - Journal of …, 2020 - thejns.org
Focal cortical dysplasia type II (FCD II) is a common histopathological substrate of epilepsy
surgery. Here, the authors propose a sulcus-centered resection strategy for this …