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20142023
most citedExplainable artificial intelligence (XAI) in deep learning-based medical image analysis

1.3k citations · 6.1k across the 35 of their papers we have counts for

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13 papers · 1 filter

eess.IV2022★ 8 cited

Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection

Ishaan Bhat, Josien P. W. Pluim, Max A. Viergever +1

Deep learning techniques show success in detecting objects in medical images, but still suffer from false-positive predictions that may hinder accurate diagnosis. The estimated unc…

eess.IV2022★ 3 cited

Generative Models for Reproducible Coronary Calcium Scoring

Sanne G. M. van Velzen, Bob D. de Vos, Julia M. H. Noothout +3

Purpose: Coronary artery calcium (CAC) score, i.e. the amount of CAC quantified in CT, is a strong and independent predictor of coronary heart disease (CHD) events. However, CAC sc…

eess.IV2021★ 1.3k cited

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis

Bas H. M. van der Velden, Hugo J. Kuijf, Kenneth G. A. Gilhuijs +1

With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis.…

eess.IV2020★ 53 cited

Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT

Steffen Bruns, Jelmer M. Wolterink, Richard A. P. Takx +5

Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic…

eess.IV2020★ 122 cited

Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images

Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +6

In this study, we propose a fast and accurate method to automatically localize anatomical landmarks in medical images. We employ a global-to-local localization approach using fully…

eess.IV2019

Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis

Majd Zreik, Tim Leiner, Nadieh Khalili +5

Treatment of patients with obstructive coronary artery disease is guided by the functional significance of a coronary artery stenosis. Fractional flow reserve (FFR), measured durin…

eess.IV2019★ 31 cited

Liver segmentation and metastases detection in MR images using convolutional neural networks

Mariëlle J. A. Jansen, Hugo J. Kuijf, Maarten Niekel +4

Primary tumors have a high likelihood of developing metastases in the liver and early detection of these metastases is crucial for patient outcome. We propose a method based on con…

eess.IV2019★ 23 cited

Harmonization of diffusion MRI datasets with adaptive dictionary learning

Samuel St-Jean, Max A. Viergever, Alexander Leemans

Diffusion magnetic resonance imaging is a noninvasive imaging technique that can indirectly infer the microstructure of tissues and provide metrics which are subject to normal vari…

eess.IV2019

Vertebra partitioning with thin-plate spline surfaces steered by a convolutional neural network

Nikolas Lessmann, Jelmer M. Wolterink, Majd Zreik +3

Thin-plate splines can be used for interpolation of image values, but can also be used to represent a smooth surface, such as the boundary between two structures. We present a meth…

eess.IV2019

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks

N. Khalili, N. Lessmann, E. Turk +6

MR images of fetuses allow clinicians to detect brain abnormalities in an early stage of development. The cornerstone of volumetric and morphologic analysis in fetal MRI is segment…

eess.IV2019★ 2 cited

Generative adversarial network for segmentation of motion affected neonatal brain MRI

N. Khalili, E. Turk, M. Zreik +3

Automatic neonatal brain tissue segmentation in preterm born infants is a prerequisite for evaluation of brain development. However, automatic segmentation is often hampered by mot…

eess.IV2019★ 29 cited

Automated characterization of noise distributions in diffusion MRI data

Samuel St-Jean, Alberto De Luca, Chantal M. W. Tax +2

Knowledge of the noise distribution in diffusion MRI is the centerpiece to quantify uncertainties arising from the acquisition process. Accurate estimation beyond textbook distribu…

eess.IV2019★ 1 cited

Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography

Majd Zreik, Robbert W. van Hamersvelt, Nadieh Khalili +5

In patients with obstructive coronary artery disease, the functional significance of a coronary artery stenosis needs to be determined to guide treatment. This is typically establi…