Erasmus MC

∙ Rotterdam , Netherlands ∙ 0 followers

" Furthermore, the hospital is the largest of the eight university medical centers in the Netherlands, both in terms of turnover and number of beds.

Featured Researchers

Bo Li
276 publications
Marleen de Bruijne
37 publications
Stefan Klein
24 publications
Florian Dubost
15 publications
Esther E. Bron
12 publications
Shuai Chen
11 publications
Christos Strydis
8 publications
Marion Smits
7 publications
Vikram Venkatraghavan
6 publications
Muhammad Ali Siddiqi
5 publications
Aad van der Lugt
5 publications

∙ 08/26/2019

Reproducible White Matter Tract Segmentation Using 3D U-Net on a Large-scale DTI Dataset

Tract-specific diffusion measures, as derived from brain diffusion MRI, ...

Bo Li, et al. ∙

∙ 08/29/2021

Variational voxelwise rs-fMRI representation learning: Evaluation of sex, age, and neuropsychiatric signatures

We propose to apply non-linear representation learning to voxelwise rs-f...

Eloy Geenjaar, et al. ∙

∙ 12/15/2021

Ten years of image analysis and machine learning competitions in dementia

Machine learning methods exploiting multi-parametric biomarkers, especia...

Esther E. Bron, et al. ∙

∙ 12/28/2020

Longitudinal diffusion MRI analysis using Segis-Net: a single-step deep-learning framework for simultaneous segmentation and registration

This work presents a single-step deep-learning framework for longitudina...

Bo Li, et al. ∙

∙ 08/14/2018

Automatic Airway Segmentation in chest CT using Convolutional Neural Networks

Segmentation of the airway tree from chest computed tomography (CT) imag...

A. Garcia-Uceda Juarez, et al. ∙

∙ 08/26/2019

A hybrid deep learning framework for integrated segmentation and registration: evaluation on longitudinal white matter tract changes

To accurately analyze changes of anatomical structures in longitudinal i...

Bo Li, et al. ∙

∙ 09/22/2021

A Quantitative Comparison of Epistemic Uncertainty Maps Applied to Multi-Class Segmentation

Uncertainty assessment has gained rapid interest in medical image analys...

Robin Camarasa, et al. ∙

∙ 12/05/2016

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

Objective: The advent of High-Performance Computing (HPC) in recent year...

Georgios Smaragdos, et al. ∙

∙ 07/17/2017

Fully Automatic and Real-Time Catheter Segmentation in X-Ray Fluoroscopy

Augmenting X-ray imaging with 3D roadmap to improve guidance is a common...

Pierre Ambrosini, et al. ∙

∙ 02/21/2017

A Discriminative Event Based Model for Alzheimer's Disease Progression Modeling

The event-based model (EBM) for data-driven disease progression modeling...

Vikram Venkatraghavan, et al. ∙

∙ 01/18/2017

Transfer learning for multi-center classification of chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a lung disease which can...

Veronika Cheplygina, et al. ∙

∙ 02/16/2018

3D Regression Neural Network for the Quantification of Enlarged Perivascular Spaces in Brain MRI

Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging...

Florian Dubost, et al. ∙

∙ 02/27/2018

Integrating Latent Classes in the Bayesian Shared Parameter Joint Model of Longitudinal and Survival Outcomes

Cystic fibrosis is a chronic lung disease which requires frequent patien...

Eleni-Rosalina Andrinopoulou, et al. ∙

∙ 08/10/2018

Disease Progression Timeline Estimation for Alzheimer's Disease using Discriminative Event Based Modeling

Alzheimer's Disease (AD) is characterized by a cascade of biomarkers bec...

Vikram Venkatraghavan, et al. ∙

∙ 11/08/2018

An End-to-end Approach to Semantic Segmentation with 3D CNN and Posterior-CRF in Medical Images

Fully-connected Conditional Random Field (CRF) is often used as post-pro...

Shuai Chen, et al. ∙

∙ 03/08/2019

Event-Based Modeling with High-Dimensional Imaging Biomarkers for Estimating Spatial Progression of Dementia

Event-based models (EBM) are a class of disease progression models that ...

Vikram Venkatraghavan, et al. ∙

∙ 04/15/2019

Towards Realistic Battery-DoS Protection of Implantable Medical Devices

Modern Implantable Medical Devices (IMDs) feature wireless connectivity,...

Muhammad Ali Siddiqi, et al. ∙

∙ 04/15/2019

POSTER: IMD Security vs. Energy: Are we tilting at windmills?

Implantable Medical Devices (IMDs) such as pacemakers and neurostimulato...

Muhammad Ali Siddiqi, et al. ∙

∙ 04/15/2019

IMD Security vs. Energy: Are We Tilting at Windmills?: POSTER

Implantable Medical Devices (IMDs) such as pacemakers and neurostimulato...

Muhammad Ali Siddiqi, et al. ∙

∙ 06/05/2019

Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks

Weakly supervised detection methods can infer the location of target obj...

Florian Dubost, et al. ∙

∙ 07/29/2019

Automated Lesion Detection by Regressing Intensity-Based Distance with a Neural Network

Localization of focal vascular lesions on brain MRI is an important comp...

Kimberlin M. H. van Wijnen, et al. ∙

∙ 08/22/2019

A joint 3D UNet-Graph Neural Network-based method for Airway Segmentation from chest CTs

We present an end-to-end deep learning segmentation method by combining ...

Antonio Garcia-Uceda Juarez, et al. ∙

∙ 09/25/2019

Towards continuous learning for glioma segmentation with elastic weight consolidation

When finetuning a convolutional neural network (CNN) on data from a new ...

Karin van Garderen, et al. ∙

∙ 02/21/2020

IMDfence: Architecting a Secure Protocol for Implantable Medical Devices

Over the past decade, focus on the security and privacy aspects of impla...

Muhammad Ali Siddiqi, et al. ∙

∙ 04/15/2020

Extending Unsupervised Neural Image Compression With Supervised Multitask Learning

We focus on the problem of training convolutional neural networks on gig...

David Tellez, et al. ∙

∙ 05/13/2020

Towards segmentation and spatial alignment of the human embryonic brain using deep learning for atlas-based registration

We propose an unsupervised deep learning method for atlas based registra...

Wietske A. P. Bastiaansen, et al. ∙

∙ 06/01/2020

Real-Time Face and Landmark Localization for Eyeblink Detection

Pavlovian eyeblink conditioning is a powerful experiment used in the fie...

Paul Bakker, et al. ∙

∙ 08/19/2021

Reproducible radiomics through automated machine learning validated on twelve clinical applications

Radiomics uses quantitative medical imaging features to predict clinical...

Martijn P. A. Starmans, et al. ∙

∙ 01/17/2022

Assessing the Security of the IEEE 802.15.6 Standard for Medical BANs

Medical Body Area Networks (MBANs) are ensembles of collaborating, poten...

Georg Hahn, et al. ∙