336 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of AmsterdamNL35 papers
- Vrije Universiteit AmsterdamNL22 papers
- Amsterdam NeuroscienceNL12 papers
- University College LondonGB10 papers
- Delft University of TechnologyNL9 papers
- Leiden University Medical CenterNL9 papers
- Erasmus MCNL8 papers
- Radboud University NijmegenNL8 papers
- University Medical Center UtrechtNL8 papers
- Leiden UniversityNL7 papers
- Erasmus University RotterdamNL5 papers
- KU LeuvenBE5 papers
9 papers · 1 filter
Towards Trustworthy AI for Glioma Diagnosis: A Task-Aware Evaluation of Uncertainty Quantification
Gonzalo Esteban Mosquera Rojas, Sebastian R. van der Voort, Carolin M. Pirkl +3
Uncertainty Quantification (UQ) is a key requirement for trustworthy AI in high-stakes medical image analysis. In this work, we evaluate UQ in a multi-task Deep Learning framework…
SMART: A Flexible, Interpretable, and Scalable Spatio-temporal Brain Atlas from High-Resolution Imaging Data
John Kalkhof, Boris Gutman, Emile d'Angremont +2
We introduce SMART, a framework for learning a flexible, interpretable, and scalable spatio-temporal brain atlas from longitudinal high-resolution 3D medical images. Existing appro…
Robust Alignment of the Human Embryo in 3D Ultrasound using PCA and an Ensemble of Heuristic, Atlas-based and Learning-based Classifiers Evaluated on the Rotterdam Periconceptional Cohort
Nikolai Herrmann, Marcella C. Zijta, Stefan Klein +5
Standardized alignment of the embryo in three-dimensional (3D) ultrasound images aids prenatal growth monitoring by facilitating standard plane detection, improving visualization o…
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…
CNN Attention Guidance for Improved Orthopedics Radiographic Fracture Classification
Zhibin Liao, Kewen Liao, Haifeng Shen +6
Convolutional neural networks (CNNs) have gained significant popularity in orthopedic imaging in recent years due to their ability to solve fracture classification problems. A comm…
Prediction of the Facial Growth Direction is Challenging
Stanisław Kaźmierczak, Zofia Juszka, Vaska Vandevska-Radunovic +3
Facial dysmorphology or malocclusion is frequently associated with abnormal growth of the face. The ability to predict facial growth (FG) direction would allow clinicians to prepar…
Automatic Landmarks Correspondence Detection in Medical Images with an Application to Deformable Image Registration
Monika Grewal, Jan Wiersma, Henrike Westerveld +2
Purpose: Deformable Image Registration (DIR) can benefit from additional guidance using corresponding landmarks in the images. However, the benefits thereof are largely understudie…
A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study
Ahmed El-Gazzar, Mirjam Quaak, Leonardo Cerliani +3
Functional Magnetic Resonance Imaging (fMRI) captures the temporal dynamics of neural activity as a function of spatial location in the brain. Thus, fMRI scans are represented as 4…
Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning
David Robben, Anna M. M. Boers, Henk A. Marquering +9
CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the p…