2 citations · 4 across the 9 of their papers we have counts for
9 papers
Do Medical Foundation Models Generalize on the African Brain?
Kaouther Mouheb, Gonzalo Esteban Mosquera Rojas, Juancito van Leeuwen +2
Medical foundation models (FMs) are increasingly used for brain MRI analysis. However, their evaluation remains dominated by high-resource datasets, leaving generalization to Afric…
Cross-Attention Multimodal Learning for Predicting Response to Neoadjuvant Imatinib in Gastrointestinal Stromal Tumors: A Multicenter Retrospective Study
Fariba Tohidinezhad, Douwe J. Spaanderman, Natalia Oviedo Acosta +14
Background: Response to neoadjuvant imatinib in gastrointestinal stromal tumors (GISTs) is highly variable and cannot be reliably predicted using current clinical or molecular mark…
Automatic Extraction of Structured Information from Brain MRI Reports Using an Open-Weight Large Language Model
Kaouther Mouheb, Amos Pomp, Antoine Manenti +9
Objectives: Automatic data extraction from free-text radiology reports enables large-scale research, but few studies assessed the performance of large language models (LLMs) on Dut…
TriALS: Triphasic-Aided Liver Lesion Segmentation Benchmark in Non-Contrast CT
Marawan Elbatel, Mohamed Ghonim, Jiaji Mao +62
Automated segmentation of liver lesions on non-contrast computed tomography (NCCT) is clinically important but fundamentally challenging, particularly in low-resource settings acro…
MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection
Marawan Elbatel, Anbang Wang, Keyuan Liu +6
This paper does not introduce a novel architecture; instead, it revisits a fundamental yet overlooked baseline: adapting human-centric foundation models for anatomical landmark det…
Evaluating Open-Weight Large Language Models for Structured Data Extraction from Narrative Medical Reports Across Multiple Use Cases and Languages
Douwe J. Spaanderman, Karthik Prathaban, Petr Zelina +20
Large language models (LLMs) are increasingly used to extract structured information from free-text clinical records, but prior work often focuses on single tasks, limited models,…
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…
Evaluating the Fairness of Neural Collapse in Medical Image Classification
Kaouther Mouheb, Marawan Elbatel, Stefan Klein +1
Deep learning has achieved impressive performance across various medical imaging tasks. However, its inherent bias against specific groups hinders its clinical applicability in equ…
Large Intestine 3D Shape Refinement Using Point Diffusion Models for Digital Phantom Generation
Kaouther Mouheb, Mobina Ghojogh Nejad, Lavsen Dahal +4
Accurate 3D modeling of human organs is critical for constructing digital phantoms in virtual imaging trials. However, organs such as the large intestine remain particularly challe…