121 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Maastricht UniversityNL11 papers
- Maastro ClinicNL7 papers
- Erasmus MCNL6 papers
- Eindhoven University of TechnologyNL4 papers
- Erasmus University RotterdamNL4 papers
- Centraal Bureau voor de StatistiekNL3 papers
- Harvard UniversityUS3 papers
- Radboud University NijmegenNL3 papers
- University Medical Center UtrechtNL3 papers
- Amsterdam NeuroscienceNL2 papers
- Amsterdam UMC Location University of AmsterdamNL2 papers
- Amsterdam University Medical CentersNL2 papers
27 papers
From mesons to the baryon asymmetry: a unified Mesogenesis Framework
M. Burgos Marcos, A. Verheyden, K. K. Vos
mesogenesis offers an interesting mechanism to generate the baryon asymmetry of the universe by converting the CP violation of the Standard Model into a net baryon number asymm…
Light-sheet microscopy in cancer pathology: current applications, clinical challenges and future perspectives
Uma Pisarović, Taichi Ochi, Iryna Samarska +8
Light-sheet fluorescence microscopy (LSFM) has emerged as a powerful research technology for three-dimensional (3D) visualization of biological tissues and is increasingly applied…
Millennium Pathways for Tractography: 40 grand challenges to shape the future of tractography
Maxime Descoteaux, Kurt G. Schilling, Dogu Baran Aydogan +44
In the spirit of the historic Millennium Prize Problems that heralded a new era for mathematics, the newly formed International Society for Tractography (IST) has launched the Mill…
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…
CLAIRE-DSA: Fluoroscopic Image Classification for Quality Assurance of Computer Vision Pipelines in Acute Ischemic Stroke
Cristo J. van den Berg, Frank G. te Nijenhuis, Mirre J. Blaauboer +9
Computer vision models can be used to assist during mechanical thrombectomy (MT) for acute ischemic stroke (AIS), but poor image quality often degrades performance. This work prese…
Optimising MFCC parameters for the automatic detection of respiratory diseases
Yuyang Yan, Sami O. Simons, Loes van Bemmel +3
Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acous…
Preictal Period Optimization for Deep Learning-Based Epileptic Seizure Prediction
Petros Koutsouvelis, Bartlomiej Chybowski, Alfredo Gonzalez-Sulser +2
Accurate prediction of epileptic seizures could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. Although deep learning-based approaches…
Federated Bayesian Network Ensembles
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Ensemble-based learning works by t…
VertiBayes: Learning Bayesian network parameters from vertically partitioned data with missing values
Florian van Daalen, Lianne Ippel, Andre Dekker +1
Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are probabilistic graphical models that have been widely used in art…
CAVE: Cerebral Artery-Vein Segmentation in Digital Subtraction Angiography
Ruisheng Su, P. Matthijs van der Sluijs, Yuan Chen +7
Cerebral X-ray digital subtraction angiography (DSA) is a widely used imaging technique in patients with neurovascular disease, allowing for vessel and flow visualization with high…
Network analyses reveal negative link between changes in adipose tissue GDF15 and BMI during dietary-induced weight loss
Alyssa Imbert, Nathalie Vialaneix, Julien Marquis +14
Adipose tissue (AT) transcriptome studies provide holistic pictures of adaptation to weight and related bioclinical settings changes. Objective To implement AT gene expression prof…
Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis
Sergey Primakov, Elizaveta Lavrova, Zohaib Salahuddin +2
Medical image analysis plays a key role in precision medicine as it allows the clinicians to identify anatomical abnormalities and it is routinely used in clinical assessment. Data…
Privacy preserving n-party scalar product protocol
Florian van Daalen, Inigo Bermejo, Lianne Ippel +1
Privacy-preserving machine learning enables the training of models on decentralized datasets without the need to reveal the data, both on horizontal and vertically partitioned data…
A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation
Robin Camarasa, Daniel Bos, Jeroen Hendrikse +4
Uncertainty assessment has gained rapid interest in medical image analysis. A popular technique to compute epistemic uncertainty is the Monte-Carlo (MC) dropout technique. From a n…
Reducing Line-of-block Artifacts in Cardiac Activation Maps Estimated Using ECG Imaging: A Comparison of Source Models and Estimation Methods
Steffen Schuler, Matthias Schaufelberger, Laura R. Bear +9
Objective: To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoB…
Multiscale modelling of reversed Potts shunt as a potential palliative treatment for suprasystemic idiopathic pulmonary artery hypertension in children
Sanjay Pant, Aleksander Sizarov, Angela Knepper1 +4
Reversed Potts shunt (PS) was suggested as palliation for patients with suprasystemic pulmonary arterial hypertension (PAH) and right ventricular (RV) failure. PS, however, can res…
Generative Models Improve Radiomics Reproducibility in Low Dose CTs: A Simulation Study
Junhua Chen, Chong Zhang, Alberto Traverso +4
Radiomics is an active area of research in medical image analysis, the low reproducibility of radiomics has limited its applicability to clinical practice. This issue is especially…
Lung Cancer Diagnosis Using Deep Attention Based on Multiple Instance Learning and Radiomics
Junhua Chen, Haiyan Zeng, Chong Zhang +4
Early diagnosis of lung cancer is a key intervention for the treatment of lung cancer computer aided diagnosis (CAD) can play a crucial role. However, most published CAD methods tr…
Probing the pH microenvironment of mesenchymal stromal cell cultures on additive-manufactured scaffolds
Ivan Lorenzo Moldero, Anil Chandra, Marta Cavo +5
Despite numerous advances in the field of tissue engineering and regenerative medicine, monitoring the formation of tissue regeneration and its metabolic variations during culture…
Nine Recommendations for Decision Aid Implementation from the Clinician Perspective
Anshu Ankolekar, Ben G. L. Vanneste, Esther Bloemen-van Gurp +9
Background: Shared decision-making (SDM) aims to empower patients to take an active role in their treatment choices, supported by clinicians and patient decision aids (PDAs). The p…
A Revision of the Bernoulli Equation as a Controller of the Fick's Diffusion Equation in Drug Delivery Modeling
Ali Esmaeili, Saeed Ranjbar
Mathematical equations can be used as effectual tools in drug delivery systems modeling and are also highly helpful to have a theoretical understanding of controlled drug release a…
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…
Simulation assisted machine learning
Timo M. Deist, Andrew Patti, Zhaoqi Wang +3
Motivation: In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making predictions. When sufficient sys…
Detecting functional decline from normal ageing to dementia: development and validation of a short version of the Amsterdam IADL Questionnaire
Roos J. Jutten, Carel F. W. Peeters, Sophie M. J. Leijdesdorff +5
INTRODUCTION: Detecting functional decline from normal ageing to dementia is relevant for diagnostic and prognostic purposes. Therefore, the Amsterdam IADL Questionnaire (A-IADL-Q)…