Marleen de Bruijne

research

∙ 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. ∙

research

∙ 11/20/2020

Crowdsourcing Airway Annotations in Chest Computed Tomography Images

Measuring airways in chest computed tomography (CT) scans is important f...

Veronika Cheplygina, et al. ∙

research

∙ 06/26/2020

Region-of-interest guided Supervoxel Inpainting for Self-supervision

Self-supervised learning has proven to be invaluable in making best use ...

Subhradeep Kayal, et al. ∙

research

∙ 11/04/2019

Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations

The scarcity of labeled data often limits the application of supervised ...

Gerda Bortsova, et al. ∙

research

∙ 11/04/2019

Automated Estimation of the Spinal Curvature via Spine Centerline Extraction with Ensembles of Cascaded Neural Networks

Scoliosis is a condition defined by an abnormal spinal curvature. For di...

Florian Dubost, et al. ∙

research

∙ 09/19/2019

APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network

Deep learning has been successfully demonstrated in MRI reconstruction o...

Chaoping Zhang, et al. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 07/29/2019

Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation

We propose a novel semi-supervised image segmentation method that simult...

Shuai Chen, et al. ∙

research

∙ 07/01/2019

Automated Image Registration Quality Assessment Utilizing Deep-learning based Ventricle Extraction in Clinical Data

Registration is a core component of many imaging pipelines. In case of c...

Florian Dubost, et al. ∙

research

∙ 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. ∙

research

∙ 03/11/2019

A cross-center smoothness prior for variational Bayesian brain tissue segmentation

Suppose one is faced with the challenge of tissue segmentation in MR ima...

Wouter M. Kouw, et al. ∙

research

∙ 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. ∙

research

∙ 11/21/2018

Graph Refinement based Tree Extraction using Mean-Field Networks and Graph Neural Networks

Graph refinement, or the task of obtaining subgraphs of interest from ov...

Raghavendra Selvan, et al. ∙

research

∙ 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. ∙

research

∙ 10/17/2018

Learning to quantify emphysema extent: What labels do we need?

Accurate assessment of pulmonary emphysema is crucial to assess disease ...

Silas Nyboe Ørting, et al. ∙

research

∙ 07/23/2018

Deep Learning from Label Proportions for Emphysema Quantification

We propose an end-to-end deep learning method that learns to estimate em...

Gerda Bortsova, et al. ∙

research

∙ 07/12/2018

Hydranet: Data Augmentation for Regression Neural Networks

Despite recent efforts, deep learning techniques remain often heavily de...

Florian Dubost, et al. ∙

research

∙ 06/23/2018

Extracting Tree-structures in CT data by Tracking Multiple Statistically Ranked Hypotheses

In this work, we adapt a method based on multiple hypothesis tracking (M...

Raghavendra Selvan, et al. ∙

research

∙ 06/19/2018

Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans

Supervised feature learning using convolutional neural networks (CNNs) c...

Silas Nyboe Ørting, et al. ∙

research

∙ 04/17/2018

Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis

Machine learning (ML) algorithms have made a tremendous impact in the fi...

Veronika Cheplygina, et al. ∙

research

∙ 04/12/2018

Extraction of Airways using Graph Neural Networks

We present extraction of tree structures, such as airways, from image da...

Raghavendra Selvan, et al. ∙

research

∙ 04/10/2018

Mean Field Network based Graph Refinement with application to Airway Tree Extraction

We present tree extraction in 3D images as a graph refinement task, of o...

Raghavendra Selvan, et al. ∙

research

∙ 03/21/2018

Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks

Cystic fibrosis is a genetic disease which may appear in early life with...

Filipe Marques, et al. ∙

research

∙ 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. ∙

research

∙ 08/07/2017

Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Segmenting tree structures is common in several image processing applica...

Raghavendra Selvan, et al. ∙

research

∙ 06/07/2017

Early Experiences with Crowdsourcing Airway Annotations in Chest CT

Measuring airways in chest computed tomography (CT) images is important ...

Veronika Cheplygina, et al. ∙

research

∙ 06/07/2017

Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images

A method for automatically quantifying emphysema regions using High-Reso...

Isabel Pino Peña, et al. ∙

research

∙ 06/04/2017

Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks

Intracranial carotid artery calcification (ICAC) is a major risk factor ...

Gerda Bortsova, et al. ∙

research

∙ 05/22/2017

GP-Unet: Lesion Detection from Weak Labels with a 3D Regression Network

We propose a novel convolutional neural network for lesion detection fro...

Florian Dubost, et al. ∙

research

∙ 03/15/2017

Label Stability in Multiple Instance Learning

We address the problem of instance label stability in multiple instance ...

Veronika Cheplygina, et al. ∙

research

∙ 03/15/2017

Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners

Supervised learning has been very successful for automatic segmentation ...

Veronika Cheplygina, et al. ∙

research

∙ 03/15/2017

Classification of COPD with Multiple Instance Learning

Chronic obstructive pulmonary disease (COPD) is a lung disease where ear...

Veronika Cheplygina, et al. ∙

research

∙ 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. ∙

research

∙ 11/24/2016

Extraction of airway trees using multiple hypothesis tracking and template matching

Knowledge of airway tree morphology has important clinical applications ...

Raghavendra Selvan, et al. ∙

research

∙ 03/29/2013

Geometric tree kernels: Classification of COPD from airway tree geometry

Methodological contributions: This paper introduces a family of kernels ...

Aasa Feragen, et al. ∙

research

∙ 07/23/2012

Towards a theory of statistical tree-shape analysis

In order to develop statistical methods for shapes with a tree-structure...

Aasa Feragen, et al. ∙

Marleen de Bruijne

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