309 citations · 311 across the 7 of their papers we have counts for
7 papers
Federated Fine-tuning of SAM-Med3D for MRI-based Dementia Classification
Kaouther Mouheb, Marawan Elbatel, Janne Papma +8
While foundation models (FMs) offer strong potential for AI-based dementia diagnosis, their integration into federated learning (FL) systems remains underexplored. In this benchmar…
GL-ICNN: An End-To-End Interpretable Convolutional Neural Network for the Diagnosis and Prediction of Alzheimer's Disease
Wenjie Kang, Lize Jiskoot, Peter De Deyn +8
Deep learning methods based on Convolutional Neural Networks (CNNs) have shown great potential to improve early and accurate diagnosis of Alzheimer's disease (AD) dementia based on…
An Interpretable Machine Learning Model with Deep Learning-based Imaging Biomarkers for Diagnosis of Alzheimer's Disease
Wenjie Kang, Bo Li, Janne M. Papma +9
Machine learning methods have shown large potential for the automatic early diagnosis of Alzheimer's Disease (AD). However, some machine learning methods based on imaging data have…
Prior-knowledge-informed deep learning for lacune detection and quantification using multi-site brain MRI
Bo Li, Jeroen de Bresser, Wiro Niessen +5
Lacunes of presumed vascular origin, also referred to as lacunar infarcts, are important to assess cerebral small vessel disease and cognitive diseases such as dementia. However, v…
Cross-Cohort Generalizability of Deep and Conventional Machine Learning for MRI-based Diagnosis and Prediction of Alzheimer's Disease
Esther E. Bron, Stefan Klein, Janne M. Papma +14
This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of…
Patient-specific fine-tuning of CNNs for follow-up lesion quantification
Mariëlle J. A. Jansen, Hugo J. Kuijf, Ashis K. Dhara +4
Convolutional neural network (CNN) methods have been proposed to quantify lesions in medical imaging. Commonly more than one imaging examination is available for a patient, but the…
Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge
Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41
Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…