Marleen de Bruijne

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Københavns Uni ∙ Erasmus MC

Associate Professor of Medical Image Analysis; Erasmus MC Rotterdam and University of Copenhagen

Crowdsourcing Airway Annotations in Chest Computed Tomography Images

Measuring airways in chest computed tomography (CT) scans is important f...
11/20/2020 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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

Self-supervised learning has proven to be invaluable in making best use ...
06/26/2020 ∙ by Subhradeep Kayal, et al. ∙ 0 ∙ share

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Semi-Supervised Medical Image Segmentation via Learning Consistency under Transformations

The scarcity of labeled data often limits the application of supervised ...
11/04/2019 ∙ by Gerda Bortsova, et al. ∙ 0 ∙ share

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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...
11/04/2019 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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

Deep learning has been successfully demonstrated in MRI reconstruction o...
09/19/2019 ∙ by Chaoping Zhang, et al. ∙ 15 ∙ share

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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 ...
08/22/2019 ∙ by Antonio Garcia-Uceda Juarez, et al. ∙ 0 ∙ share

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

Localization of focal vascular lesions on brain MRI is an important comp...
07/29/2019 ∙ by Kimberlin M. H. van Wijnen, et al. ∙ 0 ∙ share

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

We propose a novel semi-supervised image segmentation method that simult...
07/29/2019 ∙ by Shuai Chen, et al. ∙ 0 ∙ share

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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...
07/01/2019 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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

Weakly supervised detection methods can infer the location of target obj...
06/05/2019 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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

Suppose one is faced with the challenge of tissue segmentation in MR ima...
03/11/2019 ∙ by Wouter M. Kouw, et al. ∙ 0 ∙ share

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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 ...
03/08/2019 ∙ by Vikram Venkatraghavan, et al. ∙ 0 ∙ share

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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...
11/21/2018 ∙ by Raghavendra Selvan, et al. ∙ 10 ∙ share

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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...
11/08/2018 ∙ by Shuai Chen, et al. ∙ 0 ∙ share

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

Accurate assessment of pulmonary emphysema is crucial to assess disease ...
10/17/2018 ∙ by Silas Nyboe Ørting, et al. ∙ 0 ∙ share

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Deep Learning from Label Proportions for Emphysema Quantification

We propose an end-to-end deep learning method that learns to estimate em...
07/23/2018 ∙ by Gerda Bortsova, et al. ∙ 0 ∙ share

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Hydranet: Data Augmentation for Regression Neural Networks

Despite recent efforts, deep learning techniques remain often heavily de...
07/12/2018 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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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...
06/23/2018 ∙ by Raghavendra Selvan, et al. ∙ 2 ∙ share

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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...
06/19/2018 ∙ by Silas Nyboe Ørting, et al. ∙ 12 ∙ share

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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...
04/17/2018 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Extraction of Airways using Graph Neural Networks

We present extraction of tree structures, such as airways, from image da...
04/12/2018 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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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...
04/10/2018 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Quantification of Lung Abnormalities in Cystic Fibrosis using Deep Networks

Cystic fibrosis is a genetic disease which may appear in early life with...
03/21/2018 ∙ by Filipe Marques, et al. ∙ 0 ∙ share

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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...
02/16/2018 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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

Segmenting tree structures is common in several image processing applica...
08/07/2017 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Early Experiences with Crowdsourcing Airway Annotations in Chest CT

Measuring airways in chest computed tomography (CT) images is important ...
06/07/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Automatic Emphysema Detection using Weakly Labeled HRCT Lung Images

A method for automatically quantifying emphysema regions using High-Reso...
06/07/2017 ∙ by Isabel Pino Peña, et al. ∙ 0 ∙ share

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Segmentation of Intracranial Arterial Calcification with Deeply Supervised Residual Dropout Networks

Intracranial carotid artery calcification (ICAC) is a major risk factor ...
06/04/2017 ∙ by Gerda Bortsova, et al. ∙ 0 ∙ share

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

We propose a novel convolutional neural network for lesion detection fro...
05/22/2017 ∙ by Florian Dubost, et al. ∙ 0 ∙ share

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Label Stability in Multiple Instance Learning

We address the problem of instance label stability in multiple instance ...
03/15/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Transfer Learning by Asymmetric Image Weighting for Segmentation across Scanners

Supervised learning has been very successful for automatic segmentation ...
03/15/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Classification of COPD with Multiple Instance Learning

Chronic obstructive pulmonary disease (COPD) is a lung disease where ear...
03/15/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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

Chronic obstructive pulmonary disease (COPD) is a lung disease which can...
01/18/2017 ∙ by Veronika Cheplygina, et al. ∙ 0 ∙ share

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Extraction of airway trees using multiple hypothesis tracking and template matching

Knowledge of airway tree morphology has important clinical applications ...
11/24/2016 ∙ by Raghavendra Selvan, et al. ∙ 0 ∙ share

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Geometric tree kernels: Classification of COPD from airway tree geometry

Methodological contributions: This paper introduces a family of kernels ...
03/29/2013 ∙ by Aasa Feragen, et al. ∙ 0 ∙ share

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Towards a theory of statistical tree-shape analysis

In order to develop statistical methods for shapes with a tree-structure...
07/23/2012 ∙ by Aasa Feragen, et al. ∙ 0 ∙ share

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Marleen de Bruijne

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