Publications

2021

Journal Articles

1.

N. Lessmann, C.I. Sánchez, L. Beenen, L.H. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W.M. van Everdingen, P.K. Gerke, B. Geurts, H.A. Gietema, M. Groeneveld, L. van Harten, N. Hendrix, W. Hendrix, H.J. Huisman, I. Išgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. van Leeuwen, J. Meakin, M. Overkamp, T. van Rees Vellinga, E.M. van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E.T. Scholten, C. Sital, L. Stöger, J. Teuwen, K. Vaidhya Venkadesh, C. de Vente, M. Vermaat, W. Xie, B. de Wilde, M. Prokop, B. van Ginneken

Automated assessment of CO-RADS and chest CT severity scores in patients with suspected COVID-19 using artificial intelligence Journal Article

Radiology, 298 (1), pp. E18-E28, 2021.

Abstract | Links | BibTeX

Inproceedings

1.

J.M.H. Noothout, E.M. Postma, S. Boesveldt, B.D. de Vos, P.A.M. Smeets, I. Išgum

Automatic segmentation of the olfactory bulbs in MRI Inproceedings

In: SPIE Medical Imaging, pp. 115961J, 2021.

Abstract | Links | BibTeX

2.

J. Sander, B.D. de Vos, I. Išgum

Unsupervised super-resolution: creating high-resolution medical images from low-resolution anisotropic examples Inproceedings

In: SPIE Medical Imaging, pp. 115960E, 2021.

Abstract | Links | BibTeX

3.

S. Bruns, J.M. Wolterink, T.P.W. van den Boogert, J.P. Henriques, J. Baan, R.N. Planken, I. Išgum

Automatic whole-heart segmentation in 4D TAVI treatment planning CT Inproceedings

In: SPIE Medical Imaging, pp. 115960B, 2021.

Abstract | Links | BibTeX

4.

N. Hampe, J.M. Wolterink, C. Collet, R.N. Planken, I. Išgum

Graph Attention Networks for Segment Labeling in Coronary Artery Trees Inproceedings

In: SPIE Medical Imaging, pp. 115961I, 2021.

Abstract | Links | BibTeX

5.

M. Zreik, N. Hampe, T. Leiner, N. Khalili, J.M. Wolterink, M. Voskuil, M.A. Viergever, I. Išgum

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

In: SPIE Medical Imaging, pp. 115961F, 2021.

Abstract | Links | BibTeX

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2020

Journal Articles

1.

J. Sander, B.D. de Vos, I. Išgum

Automatic segmentation with detection of local segmentation failures in cardiac MRI Journal Article

Scientific Reports, 10 (21769 ), 2020.

Abstract | Links | BibTeX

2.

S. Bruns, J.M. Wolterink, R.A.P. Takx, R.W. van Hamersvelt, D. Suchá, M.A. Viergever, T. Leiner, I. Išgum

Deep learning from dual-energy information for whole-heart segmentation in dual-energy and single-energy non-contrast-enhanced cardiac CT Journal Article

Medical Physics, 47 (10), pp. 5048-5060, 2020.

Abstract | Links | BibTeX

3.

M.L. Tolhuisen, E. Ponomareva, A.M. Boers, I. Jansen, M.S. Koopman, R.S. Barros, O.A. Berkhemer, W.H. van Zwam, A. van der Lugt, C.B.L.M. Majoie; H.A. Marquering

A convolutional neural network for anterior intra ‐ arterial thrombus detection and segmentation on non ‐ contrast computed tomography of patients with acute ischemic stroke Journal Article

Applied Sciences, 10 (14), 2020.

Abstract | Links | BibTeX

4.

J.M.H. Noothout, B.D. de Vos, J.M. Wolterink, E.M. Postma, P.A.M. Smeets, R.A.P. Takx, T. Leiner, M.A. Viergever, I. Išgum

Deep learning-based regression and classification for automatic landmark localization in medical images Journal Article

IEEE Transactions on Medical Imaging, 39 (12), pp. 4011-4022, 2020, ISSN: 1558-254X.

Abstract | Links | BibTeX

5.

A. Lin, M. Kolossváry, I. Išgum, P. Maurovich-Horvat, P.J. Slomka, D. Dey

Artificial intelligence: improving the efficiency of cardiovascular imaging Journal Article

Expert Review of Medical Devices, 17 (6), pp. 565-577, 2020.

Abstract | Links | BibTeX

6.

P.J. Slomka, R.J.H. Miller, I. Išgum, D. Dey

Application and translation of artificial intelligence to cardiovascular imaging in nuclear medicine and noncontrast CT Journal Article

Seminars in Nuclear Medicine, 50 (4), pp. 357-366, 2020.

Abstract | Links | BibTeX

7.

R.S. Barros, W.E. van der Steen, A.M. Boers, I. Zijlstra, R. van den Berg, W. El Youssoufi, A. Urwald, D. Verbaan, P. Vandertop, C. Majoie,; S.D. Olabarriaga

Automated segmentation of subarachnoid hemorrhages with convolutional neural networks Journal Article

Informatics in Medicine Unlocked, 19 , 2020.

Abstract | Links | BibTeX

8.

N. Hampe, U. Katscher, C.A.T. van den Berg, K.K. Tha, S. Mandija

Investigating the challenges and generalizability of deep learning brain conductivity mapping Journal Article

Physics in Medicine & Biology, 65 (13), pp. 135001, 2020.

Abstract | Links | BibTeX

9.

M. Zreik, R.W. van Hamersvelt, N. Khalili, J.M. Wolterink, M. Voskuil, M.A. Viergever, T. Leiner, I. Išgum

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

Transactions on Medical Imaging, 39 (5), pp. 1545-1557, 2020.

Abstract | Links | BibTeX

10.

C. Celeng, R.A.P. Takx, N. Lessmann, P. Maurovich-Horvat, T. Leiner, I. Išgum, P.A. de Jong

The association between marital status, coronary computed tomography imaging biomarkers, and mortality in a lung cancer screening population Journal Article

Journal of Thoracic Imaging, 35 (3), pp. 204-209, 2020.

Abstract | Links | BibTeX

11.

C.C. van 't Klooster, H.M. Nathoe, J .Hjortnaes, M.L. Bots, I. Išgum, N. Lessmann, Y. van der Graaf, T. Leiner, F.L.J. Visseren, On behalf of the UCC-SMART-study group

Multifocal cardiovascular calcification in patients with established cardiovascular disease; prevalence, risk factors, and relation with recurrent cardiovascular disease Journal Article

International Journal of Cardiology, Heart & Vasculature, 27 (100499), 2020.

Abstract | Links | BibTeX

12.

S.W. Baalman, F.E. Schroevers, A.J. Oakley, T.F. Brouwer, W. van der Stuijt, H. Bleijendaal, L.A. Ramos, R.R. Lopes, H.A. Marquering, R.E. Knops,; J.R. de Groot

A morphology based deep learning model for atrial fibrillation detection using single cycle electrocardiographic samples. Journal Article

International Journal of Cardiology, 20 , 2020.

Abstract | Links | BibTeX

13.

I. Jansen, M. Lucas, J. Bosschieter, O.J. de Boer, S.L. Meijer, T.G. van Leeuwen, H.A. Marquering, J.A. Nieuwenhuijzen, D.M. de Bruin,; C.D. Savci-Heijink

Automated detection and grading of non-muscle-invasive urothelial cell carcinoma of the bladder Journal Article

The American journal of pathology, 190 (7), pp. 1483-1490, 2020.

Abstract | Links | BibTeX

14.

H. Prasetya, L.A. Ramos, T. Epema, K.M. Treurniet, B.J. Emmer, I.R. van den Wijngaard, G. Zhang, M. Kappelhof, O.A. Berkhemer, A.J. Yoo, Y.B.E.W.M. Roos, R.J. van Oostenbrugge, D.W.J. Dippel, W.H. van Zwam, A. van der Lugt, B.A.J.M. de Mol, C.B.L.M. Majoie, E. van Bavel, H.A. Marquering

qTICI: Quantitative assessment of brain tissue reperfusion on digital subtraction angiograms of acute ischemic stroke patients Journal Article

International Journal of Stroke, 2020.

Abstract | Links | BibTeX

15.

S.G.M. van Velzen, N. Lessmann, B.K. Velthuis, I.E.M. Bank, D.H.J.G. van den Bongard, T. Leiner, P. A. de Jong, W. B. Veldhuis, A. Correa, J.G. Terry, J.J. Carr, M.A. Viergever, H.M. Verkooijen, I. Išgum

Deep learning for automatic calcium scoring in CT: validation using multiple cardiac CT and chest CT protocols Journal Article

Radiology, 295 (1), 2020.

Abstract | Links | BibTeX

16.

C. Beijst, J. Dudink, R. Wientjes, I. Benavente-Fernandez, F. Groenendaal, M.J. Brouwer, I. Išgum, H.W.A.M. de Jong, L.S. de Vries

Two-dimensional ultrasound measurements vs. magnetic resonance imaging-derived ventricular volume of preterm infants with germinal matrix intraventricular haemorrhage Journal Article

Pediatric Radiology, 50 (2), pp. 234–241, 2020.

Abstract | Links | BibTeX

17.

J.W. Bartstra, P.A. de Jong, G. Kranenburg, J.M. Wolterink, I. Išgum, A. Wijsman, B. Wolf, A.M. den Harder, W.P.T.M. Mali, W. Spiering

Etidronate halts systemic arterial calcification in pseudoxanthoma elasticum Journal Article

Atherosclerosis, 292 , pp. 37-41, 2020.

Abstract | Links | BibTeX


Inproceedings

1.

T.F.A. van der Ouderaa, I. Išgum, W.B. Veldhuis, B.D. de Vos

Deep group-wise variational diffeomorphic image registration Inproceedings

In: MICCAI workshop on Thoracic Image Analysis , 2020.

Abstract | Links | BibTeX

2.

L.D. van Harten, J.M. Wolterink, J.J.C. Verhoeff, I. Išgum

Automatic online quality control of synthetic CTs Inproceedings

In: SPIE Medical Imaging, pp. 113131M, 2020.

Abstract | Links | BibTeX

3.

B.D. de Vos, B.H.M. van der Velden, J. Sander, K.G.A. Gilhuijs, M. Staring, I. Išgum

Mutual information for unsupervised deep learning image registration Inproceedings

In: SPIE Medical Imaging, pp. 113130R, 2020.

Abstract | Links | BibTeX

4.

S.G.M. van Velzen, B.D. de Vos, H.M. Verkooijen, T. Leiner, M.A. Viergever, I. Išgum

Coronary artery calcium scoring: can we do better? Inproceedings

In: SPIE Medical Imaging, pp. 113130G, 2020.

Abstract | Links | BibTeX

5.

L.D. van Harten, J.M. Wolterink, J.J.C. Verhoeff, I. Išgum

Exploiting clinically available delineations for CNN-based segmentation in radiotherapy treatment planning Inproceedings

In: SPIE Medical Imaging, pp. 113131F, 2020.

Abstract | Links | BibTeX

Abstracts

1.

R. Gal, S.G. van Velzen, M.J. Emaus, D.H. van den Bongard, M.L. Gregorowitsch, E.L. Blezer, G. Sofie, N. Lessmann, M.G. Sattler, M.J. Hooning, A.J. Teske, J.J. Penninkhof, H. Meijer, J.P. Pignol, J. Verloop, I. Išgum, H.M. Verkooijen, Bragatston Study Group

The risk of cardiovascular disease in irradiated breast cancer patients: The role of cardiac calcifications and adjuvant treatment Abstract

In: European Journal of Cancer, 138, pp. S6, 2020.

Abstract | Links | BibTeX

2.

M. Oudkerk Pool, B.D. De Vos, J.M. Wolterink, S. Blok, M.J. Schuuring, H. Bleijendaal, D.A.J. Dohmen, I.I. Tulevski, G.A. Somsen, B.J.M. Mulder, Y. Pinto, B.J. Bouma, I. Išgum, M.M. Winter

Distinguishing sinus rhythm from atrial fibrillation on single-lead ECGs using a deep neural network Abstract

In: 2020.

Abstract | Links | BibTeX

PhD Theses

1.

N. Khalili

Machine learning for automatic segmentation of neonatal and fetal MR brain images PhD Thesis

Utrecht University, The Netherlands, 2020, ISBN: 978-90-393-7324-8.

Links | BibTeX

2.

M. Zreik

Machine learning for coronary artery disease analysis in cardiac CT PhD Thesis

Utrecht University, The Netherlands, 2020, ISBN: 978-94-6323-978-3.

BibTeX



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2019

Journal Articles

1.

R.S. Barros, M.L. Tolhuisen, A.M. Boers. I. Jansen, E. Ponomareva, D.W. Dippel, A. van der Lugt, R.J. van Oostenbrugge, W.H. van Zwam, O.A. Berkhemer, M. Goyal, A.M. Demchuk, B.K. Menon, P. Mitchell, M.D. Hill, T.G. Jovin, A. Davalos, B.C.V. Campbell, J.L. Saver, Y.B.W.E.M. Roos, K.W. Muir, P. White, S. Bracard, F. Guillemin, S.D. Olabarriaga, C.B.L.M Majoie, H.A. Marquering

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks Journal Article

Journal of NeuroInterventional Surgery, (015471), 2019.

Abstract | Links | BibTeX

2.

A. Hilbert, L.A. Ramos, H.J.A. van Os, S.D. Olabarriaga, M.L. Tolhuisen, M.J.H. Wermer, R.S. Barros, I. van der Schaaf, D. Dippel, Y.B.W.E.M. Roos, W.H. van Zwam, A.J. Yoo, B.J. Emmer, G.J. Lycklama À Nijeholt, A.H. Zwinderman, G.J. Strijkers, C.B.L.M. Majoie, H.A. Marquering

Data-efficient deep learning of radiological image data for outcome prediction after endovascular treatment of patients with acute ischemic stroke Journal Article

Computers in Biology and Medicine, 115 , 2019.

Abstract | Links | BibTeX

3.

N. Hampe, J.M. Wolterink, S.G.M. van Velzen, T. Leiner, I. Išgum

Machine learning for assessment of coronary artery disease in cardiac CT: a survey Journal Article

Frontiers in Cardiovascular Medicine, 6 (172), 2019.

Abstract | Links | BibTeX

4.

M. Dekker, F. Waissi, I.E.M. Bank, N. Lessmann, I. Išgum, B.K. Velthuis, A.M. Scholtens, G.E. Leenders, G. Pasterkamp, D.P.V. de Kleijn, L. Timmers, A. Mosterd

Automated calcium scores collected during myocardial perfusion imaging improve identification of obstructive coronary artery disease Journal Article

International Journal of Cardiology, 26 (100434), 2019.

Abstract | Links | BibTeX

5.

M. Lucas, E.I. Liem, C.D. Savci-Heijink, J.E. Freund, H.A. Marquering, T.G. van Leeuwen; D.M. de Bruin

Toward Automated In Vivo Bladder Tumor Stratification Using Confocal Laser Endomicroscopy Journal Article

Journal of Endourology, 33 (11), pp. 930-937, 2019.

Abstract | Links | BibTeX

6.

N. Khalili, E.Turk, M.J.N.L. Benders, P. Moeskops, N.H.P. Claessens, R. de Heuse, A. Franx, N. Wagenaar, J.M.P.J. Breur, M.A. Viergever, I. Išgum

Automatic extraction of the intracranial volume in fetal and neonatal MR scans using convolutional neural networks Journal Article

NeuroImage Clinical, 24 (102061), 2019.

Abstract | Links | BibTeX

7.

T. Leiner, D. Rueckert, A. Suinesiaputra, B. Baeßler, R. Nezafat, I. Išgum, A.A. Young

Machine learning in cardiovascular magnetic resonance: basic concepts and applications Journal Article

Journal of Cardiovascular Magnetic Resonance, 21 (1), pp. 61, 2019.

Abstract | Links | BibTeX

8.

S.R. Zwakenberg, P.A. de Jong, J.W. Bartstra, R. van Asperen, J. Westerink, H. de Valk, R.H.J.A. Slart, G. Luurtsema, J.M. Wolterink, G.J. de Borst, J.A. van Herwaarden, M.A. van de Ree, L.J. Schurgers, Y.T. van der Schouw, J.W.J. Beulens

The effect of menaquinone-7 supplementation on vascular calcification in patients with diabetes: a randomized, double-blind, placebo-controlled trial Journal Article

The American Journal of Clinical Nutrition, 2019.

Abstract | Links | BibTeX

9.

G. Litjens, F. Ciompi, J.M. Wolterink, B.D. de Vos, T. Leiner, J. Teuwen, I. Išgum

State-of-the-art deep learning in cardiovascular image analysis Journal Article

JACC: Cardiovascular Imaging, 12 (8 Part 1), pp. 1549-1565, 2019.

Abstract | Links | BibTeX

10.

M.J. Emaus, I. Išgum, S.G.M. van Velzen, H.J.G.D. van den Bongard, S.A.M. Gernaat, N. Lessmann, M.G.A. Sattler, A.J. Teske, J. Penninkhof, H. Meijer, J.P. Pignol, H.M. Verkooijen; Bragatston study group

Bragatston study protocol: a multicentre cohort study on automated quantification of cardiovascular calcifications on radiotherapy planning CT scans for cardiovascular risk prediction in patients with breast cancer Journal Article

BMJ Open, 9 (7), pp. e028752, 2019.

Abstract | Links | BibTeX

11.

E. Verburg, J.M. Wolterink, S.N. de Waard, I. Išgum, C.H. van Gils, W.B. Veldhuis, K.G.A. Gilhuijs

Knowledge-based and deep learning-based automated chest wall segmentation in Magnetic Resonance Images of extremely dense breasts Journal Article

Medical physics, 46 (10), pp. 4405-4416, 2019.

Abstract | Links | BibTeX

12.

M. Lucas, I. Jansen, C.D. Savci-Heijink, S.L. Meijer, O.J. de Boer, T.G. van Leeuwen, D.M. de Bruin; H.A. Marquering

Deep learning for automatic Gleason pattern classification for grade group determination of prostate biopsies Journal Article

Virchows Archiv, 475 (1), pp. 77-83, 2019.

Abstract | Links | BibTeX

13.

B.G. Dutra, M.L. Tolhuisen, H.C.B.R. Alves, K.M. Treurniet, M. Kappelhof, A.J. Yoo, I.G.H. Jansen, D.W.J. Dippel, W.H. van Zwam, R.J. van Oostenbrugge, A.J. da Rocha, H.F. Lingsma, A. van der Lugt, Y.B.W.E.M. Roos, H.A. Marquering, C.B.L.M. Majoie, the MR CLEAN Registry Investigators

Thrombus imaging characteristics and outcomes in acute ischemic stroke patients undergoing endovascular treatment Journal Article

Stroke, 50 (8), pp. 2057–2064, 2019.

Abstract | Links | BibTeX

14.

N. Khalili, N. Lessmann, E. Turk, N. Claessens, R. de Heus, T. Kolk, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Automatic brain tissue segmentation in fetal MRI using convolutional neural networks Journal Article

Magnetic Resonance Imaging, 64 , pp. 77-89, 2019.

Abstract | Links | BibTeX

15.

J.W. Benjamins, K. van Leeuwen, L. Hofstra, M. Rienstra, Y. Appelman, W. Nijhof, B. Verlaat, I. Everts, H.M. den Ruijter, I. Išgum, T. Leiner, R. Vliegenthart, F.W. Asselbergs, L.E. Juarez-Orozco, P. van der Harst

Enhancing cardiovascular artificial intelligence (AI) research in the Netherlands: CVON-AI consortium Journal Article

Netherlands Heart Journal, 27 , pp. 414–425, 2019.

Abstract | Links | BibTeX

16.

R.R. Lopes, M.S. van Mourik, E.V. Schaft, L.A. Ramos, J. Baan Jr., J. Vendrik, B.A.J.M. de Mol, M.M. Vis & H.A. Marquering

Value of machine learning in predicting TAVI outcomes Journal Article

Netherlands Heart Journal, 27 , pp. 443–450, 2019.

Abstract | Links | BibTeX

17.

I. Jansen, M. Lucas, C.D. Savci-Heijink, S.L. Meijer, E.I. Liem, O.J. de Boer, T.G. van Leeuwen, H.A. Marquering; D.M. de Bruin

Three-dimensional histopathological reconstruction of bladder tumours Journal Article

Diagnostic pathology, 14 (1), pp. 1-7, 2019.

Abstract | Links | BibTeX

18.

M.N. Cizmeci, N. Khalili, N.H.P. Claessens, F. Groenendaal, K.D. Liem

Assessment of brain injury and brain volumes after posthemorrhagic ventricular dilatation: a nested substudy of the randomized controlled ELVIS trial Journal Article

Journal of Pediatrics, 2019.

Abstract | Links | BibTeX

19.

J.M. Wolterink

Left ventricle segmentation in the era of deep learning Journal Article

Journal of Nuclear Cardiology, 2019.

Links | BibTeX

20.

N.H.P. Claessens, N. Khalili, I. Išgum, H. ter Heide, T.J. Steenhuis, E. Turk, N.J.G. Jansen, L.S. de Vries, J.M.P.J. Breur, R. de Heus, M.J.N.L. Benders

Brain and cerebrospinal fluid volumes in fetuses and neonates with antenatal diagnosis of critical congenital heart disease: a longitudinal MRI study Journal Article

American Journal of Neuroradiology, 2019.

Abstract | Links | BibTeX

21.

B.D. de Vos, J.M. Wolterink, T. Leiner, P.A. de Jong, N. Lessmann, I. Išgum

Direct automatic coronary calcium scoring in cardiac and chest CT Journal Article

IEEE Transactions on Medical Imaging, 34 , pp. 123-136, 2019.

Abstract | Links | BibTeX

22.

B.D. de Vos; F.F. Berendsen; M.A. Viergever; H. Sokooti; M. Staring; I. Išgum

A deep learning framework for unsupervised affine and deformable image registration Journal Article

Medical Image Analysis, 52 , pp. 128 - 143, 2019.

Abstract | Links | BibTeX

23.

D.R.N. Vos, I. Jansen, M. Lucas, M.R.L. Paine, O.J. de Boer, S.L. Meijer, C.D. Savci-Heijink, H.A. Marquering, D.M. de Bruin, R.M.A. Heeren; S.R. Ellis

Strategies for managing multi-patient 3D mass spectrometry imaging data Journal Article

Journal of Proteomics, 193 , pp. 184-191, 2019.

Abstract | Links | BibTeX

24.

N. Lessmann, B. van Ginneken, P.A. de Jong, I. Išgum

Iterative fully convolutional neural networks for automatic vertebra segmentation and identification Journal Article

Medical Image Analysis, 53 , pp. 142-155, 2019.

Abstract | Links | BibTeX

25.

R.W. van Hamersvelt, I. Išgum, P.A. de Jong, M.J. Cramer, G.E. Leenders, M.J. Willemink, M. Voskuil, T. Leiner

Application of speCtraL computed tomogrAphy to impRove specIficity of cardiac compuTed tomographY (CLARITY study): Rationale and Design Journal Article

BMJ Open, 9 (3), pp. e025793, 2019.

Abstract | Links | BibTeX

26.

N. Lessmann, P.A. de Jong, C. Celeng, R.A.P. Takx, M.A. Viergever, B. van Ginneken, I. Išgum

Sex differences in coronary artery and thoracic aorta calcification and their association with cardiovascular mortality in heavy smokers Journal Article

JACC: Cardiovascular Imaging, 12 (9), pp. 1808-1817, 2019.

Abstract | Links | BibTeX

27.

J.M. Wolterink, R.W. van Hamersvelt, M.A. Viergever, T. Leiner, I. Išgum

Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier Journal Article

Medical Image Analysis, 51 , pp. 46-60, 2019.

Abstract | Links | BibTeX


Inproceedings

1.

J.M. Wolterink, T. Leiner, I. Išgum

Graph convolutional networks for coronary artery segmentation in cardiac CT angiography Inproceedings

In: Graph Learning in Medical Imaging (GLMI 2019), Lecture Notes in Computer Science, 2019.

Links | BibTeX

2.

S. Bruns, J.M. Wolterink, R.W. van Hamersvelt, T. Leiner, I. Išgum

CNN-based segmentation of the cardiac chambers and great vessels in non-contrast-enhanced cardiac CT Inproceedings

In: Medical Imaging with Deep Learning (MIDL 2019), 2019.

Abstract | Links | BibTeX

3.

M.S. Elmahdy, J.M. Wolterink, H. Sokooti, I. Išgum, M. Staring

Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy Inproceedings

In: Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Lecture Notes in Computer Science, 2019.

Abstract | Links | BibTeX

4.

N. Khalili, E. Turk, M. Zreik, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Generative adversarial network for segmentation of motion affected neonatal brain MRI Inproceedings

In: Medical Image Computing and Computer Assisted Intervention (MICCAI 2019), Lecture Notes in Computer Science, 2019.

Links | BibTeX

5.

J. Fernandes, V. Alves, N. Khalili3, M.J.N.L. Benders, I. Išgum, J. Pluim, P. Moeskops

Convolutional Neural Network-based regression for quantification of brain characteristics using MRI Inproceedings

In: WorldCist: 7th World Conference on Information Systems and Technologies , pp. 577-586, Springer, 2019.

Abstract | Links | BibTeX

6.

L.D. van Harten; J.M.H. Noothout; J.J.C. Verhoeff; J.M. Wolterink; I. Išgum

Automatic segmentation of organs at risk in thoracic CT scans by combining 2D and 3D convolutional neural networks Inproceedings

In: Proc. of SegTHOR challenge at IEEE International Symposium on Biomedical Imaging, 2019.

Abstract | Links | BibTeX

7.

B.H. van der Velden, B.D. de Vos, C. E. Loo, H.J. Kuijf, I. Išgum, K.G.A. Gilhuijs

Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing Inproceedings

In: SPIE Medical Imaging, pp. 109500D, 2019.

Abstract | Links | BibTeX

8.

S. Bruns, J.M. Wolterink, R.W. van Hamersvelt, M. Zreik, T. Leiner, I. Išgum

Improving myocardium segmentation in cardiac CT angiography using spectral information Inproceedings

In: SPIE Medical Imaging, pp. 109492M, 2019.

Abstract | Links | BibTeX

9.

S.G.M. van Velzen, M. Zreik, N. Lessmann, M.A. Viergever, P.A. de Jong, H.M. Verkooijen, I. Išgum

Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning Inproceedings

In: SPIE Medical Imaging, pp. 109490X, 2019.

Abstract | Links | BibTeX

10.

J. Sander, B.D. de Vos, J.M. Wolterink, I. Išgum

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI Inproceedings

In: SPIE Medical Imaging, pp. 1094919, 2019.

Abstract | Links | BibTeX

Conferences

1.

J.M. Wolterink, A. Mukhopadhyay, T. Leiner, T. Vogl, A. Bucher, I. Isgum

Generative Adversarial Networks (GANs): a primer for radiologists Conference

Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX


Book Chapters

1.

J. Verjans, W.B. Veldhuis, G. Carneiro, J.M. Wolterink, I. Išgum, T. Leiner

Cardiovascular Diseases Book Chapter

In: E.R. Ranschaert, S. Morozov, P.R. Algra (Ed.): Artificial Intelligence in Medical Imaging - Opportunities, Applications and Risks, pp. 167-185, Springer International Publishing, 2019, ISBN: 978-3-319-94878-2.

BibTeX


Abstracts

1.

J.M.H. Noothout, B.D. de Vos, J.M. Wolterink, R.A.P. Takx, T. Leiner, I. Išgum

Deep learning for automatic landmark localization in CTA for transcatheter aortic valve implantation Abstract

In: Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX

2.

S.G.M. van Velzen, J.G. Terry, B.D. de Vos, N Lessmann, S. Nair, A. Correa, H.M. Verkooijen J.J. Carr, I. Išgum

Automatic prediction of coronary heart disease events using coronary and thoracic aorta calcium among African Americans in the Jackson Heart study Abstract

In: Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX

3.

S.G.M. van Velzen, N. Lessmann, M.J. Emaus, H. van den Bongard, H.M. Verkooijen, I. Išgum

Deep learning for calcium scoring in radiotherapy treatment planning CT scans in breast cancer patients Abstract

In: Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX

4.

P. Moeskops, B.D. de Vos, W.B. Veldhuis, A.M. May, S. Kurk, M. Koopman, P.A. de Jong, T.Leiner, I. Išgum

Automatic quantification of 3D body composition from abdominal CT with an ensemble of convolutional neural networks Abstract

In: Radiological Society of North America, 105th Annual Meeting, 2019.

Abstract | Links | BibTeX

5.

M.D. Oudkerk Pool, J.P. Bokma , R.R. Lopes, Y. Pinto, M.M. Winter

Predicting mortality in patients with tetralogy of Fallot using machine learning Abstract

In: Scientific Autumn Congress of the Netherlands Society of Cardiology, 2019.

Abstract | Links | BibTeX

6.

M.D. Oudkerk Pool, D. Kauw, M.J. Schuuring, G.A. Somsen, I.I. Tulevski, B.J. Bouma, B.J.M. Mulder, M.M. Winter

mHealth enables early diagnosis and therapeutic intervention in patients with congenital heart disease Abstract

In: European Society of Cardiology Congress, Paris , 2019.

Abstract | BibTeX

7.

M. Froeling, L. Schlaffke, M. Rohm, I. Išgum, H. Kan, J.M. Wolterink

Evaluation of input data and UNet based convolutional network architectures for automated muscle annotation in 2D and 3D Abstract

In: International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.

Abstract | BibTeX

8.

N. Khalili, N. Lessmann, E. Turk, M.A. Viergever, M.J.N.L. Benders, I. Išgum

Brain tissue segmentation in fetal MRI using convolutional neural networks with simulated intensity inhomogeneities Abstract

In: International Society for Magnetic Resonance in Medicine, 27th Annual Meeting & Exhibition, 2019.

Abstract | BibTeX

9.

M.N. Cizmeci, N. Khalili, I. Išgum, N. Claessens, F. Groenendaal, D. Liem, A. Heep, I. B. Fernandez, I. van Straaten, G. van Wezel-Meijler, E. van ‘t Verlaat, A. Whitelaw, M.J.N.L. Benders, L.S. de Vries; the ELVIS study group

Timing of intervention for posthemorrhagic ventricular dilatation: effect on brain injury and brain volumes on term-equivalent age MRI Abstract

In: Pediatric Academic Societies Meeting 2018, 2019.

Abstract | BibTeX


PhD Theses

1.

J. Šprem

Enhanced cardiovascular risk prediction by machine learning PhD Thesis

Utrecht University, The Netherlands, 2019, ISBN: 978-94-6323-713-0.

BibTeX

2.

N. Lessmann

Machine learning based quantification of extrapulmonary diseases in chest CT PhD Thesis

Utrecht University, The Netherlands, 2019, ISBN: 978-94-6323-607-2.

BibTeX

3.

R.W. van Hamersvelt

New dimensions in cardiovascular CT PhD Thesis

Utrecht University, The Netherlands, 2019, ISBN: 978-90-393-7092-6.

BibTeX


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2018

Journal Articles

1.

J. Šprem, B.D. de Vos, N. Lessmann, R.W. van Hamersvelt, M.J.W. Greuter, P.A. de Jong, T. Leiner, M.A. Viergever, I. Išgum

Coronary calcium scoring with partial volume correction in anthropomorphic thorax phantom and screening chest CT images Journal Article

PLoS One, 13 (12), pp. e0209318, 2018.

Abstract | Links | BibTeX

2.

J. Šprem; B.D. de Vos; N. Lessmann; P.A. de Jong; M.A. Viergever; I. Išgum

Impact of automatically detected motion artifacts on coronary calcium scoring in chest CT Journal Article

Journal of Medical Imaging, 5 (4), pp. 044007 , 2018.

Abstract | Links | BibTeX

3.

M. Zreik, R.W. van Hamersvelt, J.M. Wolterink, T. Leiner, M.A. Viergever, I. Išgum

A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography Journal Article

IEEE Transactions on Medical Imaging, 38 (7), 2018.

Abstract | Links | BibTeX

4.

L.A. Ramos, W.E. van der Steen, R.S. Barros, C.B.L.M. Majoie, R. van den Berg, D. Verbaan, W.P. Vandertop, I.A.J. Jan Zijlstra, A.H. Zwinderman, G.J. Strijkers, S.D. Olabarriaga, H.A. Marquering

Machine learning improves prediction of delayed cerebral ischemia in patients with subarachnoid hemorrhage Journal Article

Journal of NeuroInterventional Surgery , 11 , pp. 497-502, 2018.

Abstract | Links | BibTeX

5.

N.H.P. Claessens, S.O. Algra, T.L. Ouwehand, N.J.G. Jansen, R. Schappin, F. Haas, M.J.C. Eijsermans, L.S. de Vries, M.J.N.L. Benders, CHD Lifespan Study Group Utrecht, P. Moeskops, I. Išgum, I.C. van Haastert, F. Groenendaal, J.M.P.J. Breur

Perioperative neonatal brain injury is associated with worse school‐age neurodevelopment in children with critical congenital heart disease Journal Article

Developmental medicine and child neurology, 60 (10), pp. 1052-1058., 2018.

Abstract | Links | BibTeX

6.

R.W. van Hamersvelt*, M. Zreik*, M. Voskuil, M.A. Viergever, I. Išgum, T. Leiner

Deep learning analysis of left ventricular myocardium in CT angiographic intermediate degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis Journal Article

European Radiology, 29 (5), pp. 2350–2359, 2018, (*equal contribution).

Abstract | Links | BibTeX

7.

H.J.A. van Os, L.A. Ramos, A. Hilbert, M.s van Leeuwen, M.A.A. van Walderveen, N.D. Kruyt, D.W.J. Dippel, E.W. Steyerberg, I.C. van der Schaaf, H.F. Lingsma, W.J. Schonewille, C.B.L.M. Majoie, S.D. Olabarriaga, K.H. Zwinderman, E. Venema, H.A. Marquering, M.J.H. Wermer, the MR CLEAN Registry Investigators

Predicting outcome of endovascular treatment for acute ischemic stroke: potential value of machine learning algorithms Journal Article

Frontiers in Neurology, 9 , pp. 784, 2018.

Abstract | Links | BibTeX

8.

A.M. den Harder, P.A. de Jong, M.C.H. de Groot, J.M. Wolterink, R.P.J. Budde, I. Išgum, W.W. van Solinge, M.J. Ten Berg, E. Lutgens, W.B. Veldhuis, S. Haitjema, I.E. Hoefer, T. Leiner

Commonly available hematological biomarkers are associated with the extent of coronary calcifications Journal Article

Atherosclerosis, 275 , pp. 166-173, 2018.

Abstract | Links | BibTeX

9.

A. Vos, G. Kranenburg, P.A. de Jong, W.P.T.M. Mali, W. van Hecke, R.L.A.W. Bleys, I. Išgum, A. Vink, W. Spiering

The amount of calcifications in pseudoxanthoma elasticum patients is underestimated in computed tomographic imaging; a post-mortem correlation of histological and computed tomographic findings in two cases Journal Article

Insights Imaging, 9 (4), pp. 493-498, 2018.

Abstract | Links | BibTeX

10.

A.M. Dinkla, J.M. Wolterink, M. Maspero, M.H.F. Savenije, J.J.C. Verhoeff, E. Seravalli, I. Išgum, P.R. Seevinck, C.A.T. van den Berg

MR-only brain radiotherapy: Dosimetric evaluation of synthetic CTs generated by a dilated convolutional neural network Journal Article

International Journal of Radiation Oncology, Biology, Physics, 102 (4), pp. 810-812, 2018.

Abstract | Links | BibTeX

11.

O. Bernard, A. Lalande, C. Zotti, F. Cervenansky, X. Yang, P. Heng, I. Cetin, K. Lekadir, O. Camaram M.A. Gonzalez Ballester, G. Sanroma, S. Napel, S. Petersen, G. Tziritas, E. Grinias, M. Khened, V.A. Kollerathu, G. Krishnamurthi, M. Rohé, X. Pennec, M. Sermesant, F. Isensee, P. Jäger, K.H. Maier-Hein, C.F. Baumgartner, L.M. Koch, J.M. Wolterink, I. Išgum, Y. Jang, Y. Hong, J. Patravali, S. Jain, O. Humbert, P. Jodoin

Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: Is the problem solved? Journal Article

IEEE Transactions on Medical Imaging, 37 (11), pp. 2514-2525, 2018.

Abstract | Links | BibTeX

12.

S.A.M. Gernaat, S.G.M. van Velzen, V. Koh, M.J. Emaus, I. Išgum, N. Lessmann, S. Moes, A. Jacobson, P.W. Tan, D.E. Grobbee, D.H.J. van den Bongard, J.I. Tang, H.M. Verkooijen

Automatic quantification of calcifications in the coronary arteries and thoracic aorta on radiotherapy planning CT scans of Western and Asian breast cancer patients Journal Article

Radiotherapy and Oncology, 127 (3), pp. 487-492, 2018.

Abstract | Links | BibTeX

13.

I. Jansen, M. Lucas, C.D. Savci-Heijink, S.L. Meijer, H.A. Marquering, D.M. de Bruin; P.J. Zondervan

Histopathology: ditch the slides, because digital and 3D are on show Journal Article

World journal of urology, 36 (4), pp. 549-555, 2018.

Abstract | Links | BibTeX

14.

N. Lessmann, B. van Ginneken, M. Zreik, P.A. de Jong, B.D. de Vos, M.A. Viergever, I. Išgum

Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions Journal Article

IEEE Transactions on Medical Imaging, 37 (2), pp. 615-625, 2018.

Abstract | Links | BibTeX

15.

M. Zreik, N. Lessmann, R.W. van Hamersvelt, J.M. Wolterink, M. Voskuil, M.A. Viergever, T. Leiner, I. Išgum

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis Journal Article

Medical Image Analysis, 44 , pp. 72-85, 2018.

Abstract | Links | BibTeX

16.

R.E.M. Senden, K. Keunen, N.E. van der Aa, A. Leemans, I. Išgum, M.A. Viergever, J. Dudink, L.S. de Vries, F. Groenendaal, M.J.N.L. Benders

Mild cerebellar injury does not significantly affect cerebral white matter microstructural organization and neurodevelopmental outcome in a contemporary cohort of preterm infants Journal Article

Pediatric Research, 83 , pp. 1004-1010, 2018.

Abstract | Links | BibTeX

17.

M.L. Tataranno, N.H.P. Claessens, P. Moeskops, M.C. Toet, K.J. Kersbergen, G. Buonocore, I. Išgum, A. Leemans, S. Counsell, F. Groenendaal, L.S. de Vries, M.J.N.L. Benders

Changes in brain morphology and microstructure in relation to early brain activity in extremely preterm infants Journal Article

Pediatric Research, 83 , pp. 834-842, 2018.

Abstract | Links | BibTeX

18.

F.J. Drost, K. Keunen, P. Moeskops, N.H.P. Claessens, F. van Kalken, I. Išgum, E.S.M. Voskuil-Kerkhof, F. Groenendaal, L.S. de Vries, M.J.N.L. Benders, J.U.M. Termote

Severe retinopathy of prematurity is associated with reduced cerebellar and brainstem volumes at term and neurodevelopmental deficits at two years Journal Article

Pediatric Research, 83 , pp. 818-824, 2018.

Abstract | Links | BibTeX

19.

J.S. Kuperus, C.F. Buckens, J. Šprem, F.C. Oner, P.A. de Jong, J. Verlaan

The Natural Course of Diffuse Idiopathic Skeletal Hyperostosis in the Thoracic Spine of Adult Males Journal Article

The Journal of Rheumatology, 2018, ISSN: 0315-162X.

Abstract | Links | BibTeX


Inproceedings

1.

J.M.H. Noothout, B.D. de Vos, J.M. Wolterink, I. Išgum

Automatic segmentation of thoracic aorta segments in low-dose chest CT Inproceedings

In: SPIE Medical Imaging, pp. 105741S, 2018.

Abstract | Links | BibTeX

2.

M. Zreik, R.W. van Hamersvelt, J.M. Wolterink, T. Leiner, M.A. Viergever, I. Išgum

Automatic Detection and Characterization of Coronary Artery Plaque and Stenosis using a Recurrent Convolutional Neural Network in Coronary CT Angiography Inproceedings

In: Medical Imaging with Deep Learning (MIDL 2018), 2018.

Abstract | Links | BibTeX

3.

N. Lessmann, B. van Ginneken, P.A. de Jong, I. Išgum

Iterative fully convolutional neural networks for automatic vertebra segmentation Inproceedings

In: Medical Imaging with Deep Learning (MIDL 2018), 2018.

Abstract | Links | BibTeX

4.

J.M. Wolterink, T. Leiner, I. Išgum

Blood vessel geometry synthesis using generative adversarial networks Inproceedings

In: Medical Imaging with Deep Learning (MIDL 2018), 2018.

Abstract | Links | BibTeX

5.

J.M.H. Noothout, B.D. de Vos, J.M. Wolterink, T. Leiner, I. Išgum

CNN-based Landmark Detection in Cardiac CTA Scans Inproceedings

In: Medical Imaging with Deep Learning (MIDL 2018), 2018.

Abstract | Links | BibTeX

6.

J.M. Wolterink, T. Leiner, M.A. Viergever, I. Išgum

Automatic segmentation and disease classification using cardiac cine MR images Inproceedings

In: Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges. STACOM 2017, pp. 101-110, Springer, Cham, 2018.

Abstract | Links | BibTeX

7.

N. Lessmann, B. van Ginneken, I. Išgum

Iterative convolutional neural networks for automatic vertebra identification and segmentation in CT images Inproceedings

In: SPIE Medical Imaging, pp. 1057408, 2018.

Abstract | Links | BibTeX


Book Chapters

1.

J.M. Wolterink, K. Kamnitsas, C. Ledig, I. Išgum

Deep learning: generative adversarial networks and adversarial methods Book Chapter

In: pp. 547-574, Handbook of Medical Image Computing and Computer Assisted Intervention, 2018.

Abstract | Links | BibTeX

2.

T. Leiner, J.M. Wolterink, I. Išgum

Artificial intelligence and cardiovascular disease - friend or foe? Book Chapter

In: J. Bremerich, R. Salgado (Ed.): The heart revealed - Radiology in the diagnosis and management of cardiac conditions , pp. 148-155 , The European Society of Radiology (ESR), 2018, ISBN: 978-3-9504388-5-7.

Links | BibTeX


Abstracts

1.

A.M. Dinkla, J.M. Wolterink, M. Maspero, M.H.F. Savenije, J.J.C. Verhoeff, I. Išgum, P.R. Seevinck, J.J.W. Lagendijk, C.A.T. van den Berg

CT synthesis for MR-only brain radiotherapy treatment planning using convolutional neural networks Abstract

In: 2018.

BibTeX

2.

A. Schreuder; C. Jacobs; N. Lessmann; E.T. Scholten; I. Išgum; M. Prokop; C.M. Schaefer-Prokop; B. van Ginneken

Improved lung cancer and mortality prediction accuracy using survival models based on semi-automatic CT image measurements Abstract

In: 2018.

BibTeX

3.

A.M. Dinkla, J.M. Wolterink, M. Maspero, M.H.F. Savenije, J.J.C. Verhoeff, I. Išgum, P.R. Seevinck, J.J.W. Lagendijk, C.A.T. van den Berg

Dosimetric evaluation of deep learning based synthetic-CT generation for MR-only brain radiotherapy Abstract

In: 2018.

BibTeX

4.

A.M. den Harder, J.M. Wolterink, P.A. de Jong, M.C.H. de Groot, R.P.J. Budde, I. Išgum, S. Haijtjema, I.E. Hoefer, T. Leiner

Basic hematological biomarkers are associated with coronary calcifications Abstract

In: 2018.

BibTeX

5.

R.W. van Hamersvelt, M. Zreik, M. Voskuil, I. Išgum, T. Leiner

Deep learning-based analysis of the left ventricular myocardium in coronary CTA images improves specificity for detection of functionally significant coronary artery stenosis Abstract

In: 2018.

Abstract | BibTeX

6.

J.M. Wolterink, I. Išgum, E. Bennink, V. Huang, M.A. Viergever, T. Leiner

Fully automatic segmentation of the renal cortex and medulla in contrast-enhanced abdominal CT using deep learning Abstract

In: 2018.

BibTeX


PhD Theses

1.

B.D. de Vos

Machine learning for cardiovascular disease analysis in chest CT PhD Thesis

Utrecht University, The Netherlands, 2018, ISBN: 978-90-393-7065-0.

BibTeX


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2017

Journal Articles

1.

M.L. Tataranno, N.H.P. Claessens, P. Moeskops, M.C. Toet, K.J. Kersbergen, G. Buonocore, I. Išgum, A. Leemans, S. Counsell, F. Groenendaal, L.S. de Vries, M.J.N.L. Benders

Changes in brain morphology and microstructure in relation to early brain activity in extremely preterm infants Journal Article

Pediatric Research, 83 (4), pp. 834-842, 2017.

Abstract | Links | BibTeX

2.

P. Moeskops, J. de Bresser, H.J Kuijf, A.M Mendrik, G.J. Biessels, J.P. Pluim, I. Išgum

Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI Journal Article

NeuroImage Clinical, 17 , pp. 251-262, 2017.

Abstract | Links | BibTeX

3.

C. Coviello, K. Keunen, K.J. Kersbergen, F. Groenendaal, A. Leemans, B. Peels, I. Isgum, M.A. Viergever, L.S. de Vries, G. Buonocore, V.P. Carnielli, M.J.N.L. Benders

Effects of early nutrition and growth on brain volumes, white matter microstructure and neurodevelopmental outcome in preterm newborns, in print Journal Article

Pediatric Research, 83 , pp. 102-110, 2017.

Abstract | Links | BibTeX

4.

I. Isgum, B.D. de Vos, J.M. Wolterink, D. Dey, D.S. Berman, M. Rubeaux, T. Leiner, P. J. Slomka

Erratum to: Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT Journal Article

Journal of Nuclear Cardiology, 25 (6), pp. 2143, 2017.

Abstract | Links | BibTeX

5.

J.M. Wolterink, T. Leiner, M.A. Viergever, I. Isgum

Generative adversarial networks for noise reduction in low-dose CT Journal Article

IEEE Transactions on Medical Imaging, 36 (12), pp. 2536 - 2545, 2017.

Abstract | Links | BibTeX

6.

P. Moeskops, I. Isgum, K. Keunen, N.H.P. Claessens, I.C. van Haastert, F. Groenendaal, L.S. de Vries, M.A. Viergever, M.J.N.L. Benders

Prediction of cognitive and motor outcome of preterm infants based on automatic quantitative descriptors from neonatal MR brain images Journal Article

Scientific Reports, 7 (2163), 2017.

Abstract | Links | BibTeX

7.

E. Pompe, P.A. de Jong, D.A. Lynch, N. Lessmann, I. Isgum, B. van Ginneken, J.-W.J. Lammers, F.A.A. Mohamed Hoesein

Computed tomographic findings in subjects who died from respiratory disease in the National Lung Screening Trial Journal Article

European Respiratory Journal, 49 , pp. 1601814, 2017.

Abstract | Links | BibTeX

8.

I. Isgum, B.D. de Vos, J.M. Wolterink, D. Dey, D.S. Berman, M. Rubeaux, T. Leiner, P.J. Slomka

Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT Journal Article

Journal of Nuclear Cardiology, 25 (6), pp. 2133-2142, 2017.

Abstract | Links | BibTeX

9.

B.D. de Vos, J.M. Wolterink, P.A. de Jong, T. Leiner, M.A. Viergever, I. Isgum

ConvNet-based localization of anatomical structures in 3D medical images Journal Article

IEEE Transactions on Medical Imaging, 36 (7), pp. 1470-1481, 2017.

Abstract | BibTeX

10.

K. Murphy, N.E. van der Aa, S. Negro, F. Groenendaal, L.S. de Vries, M.A. Viergever, G.B. Boylan, M.J.N.L. Benders, I.Isgum

Automatic quantification of ischemic injury on diffusion-weighted MRI of neonatal hypoxic ischemic encephalopathy Journal Article

NeuroImage: Clinical, 14 , pp. 222-232, 2017.

Abstract | BibTeX


Inproceedings

1.

B.D. de Vos, F.F. Berendsen, M.A. Viergever, M. Staring, I. Isgum

End-to-end unsupervised deformable image registration with a convolutional neural network Inproceedings

In: ML-CDS 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, Proceedings (Ed.): Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, pp. 204–212, ML-CDS 2017, Held in Conjunction with MICCAI 2017, Quebec City, QC, Canada, September 14, Proceedings 2017.

Abstract | Links | BibTeX

2.

H. Sokooti, B.D. de Vos, F. Berendsen, B.P.F. Lelieveldt, I. Isgum, M. Staring

Nonrigid image registration using multi-scale 3D convolutional neural networks Inproceedings

In: Medical Image Computing and Computer Assisted Intervention − MICCAI 2017: 20th International Conference, Quebec City, QC, Canada, September 11-13, 2017, Proceedings, Part 1, pp. 232–239, 2017.

Abstract | Links | BibTeX

3.

J.M. Wolterink, A.M. Dinkla, M.H.F. Savenije, P.R. Seevinck, C.A.T. van den Berg, I. Isgum

Deep MR to CT synthesis using unpaired data Inproceedings

In: SASHIMI 2017: Simulation and Synthesis in Medical Imaging, pp. 14023, 2017.

Abstract | Links | BibTeX

4.

M.L. Tolhuisen, J. Enthoven, E.M.M. Santos, W.J. Niessen, L.F.M. Beenen, D.W.J. Dippel, A. van der Lugt, W.H. van Zwam, Y.B.W.E.M. Roos, R.J. van Oostenbrugge, C.B.L.M. Majoie, H.A. Marquering

The effect of non-contrast CT slice thickness on thrombus density and perviousness assessment Inproceedings

In: Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment. RAMBO 2017, CMMI 2017, SWITCH 2017, Lecture Notes in Computer Science, pp. 168–175, 2017.

Abstract | Links | BibTeX

5.

N. Khalili, P. Moeskops, N.H.P. Claessens, S. Scherpenzeel, E. Turk, R. de Heus, M.J.N.L. Benders, M.A. Viergever, J.P.W. Pluim, I. Išgum

Automatic segmentation of the intracranial volume in fetal MR images Inproceedings

In: MICCAI Workshop on Fetal and InFant Image analysis (FIFI 2017), 2017.

Abstract | Links | BibTeX

6.

J. Šprem; B.D. de Vos; P.A. de Jong; M.A. Viergever; I. Isgum

Classification of coronary artery calcifications according to motion artifacts in chest CT using a convolutional neural network Inproceedings

In: SPIE Medical Imaging, 2017.

Abstract | Links | BibTeX

7.

J.M. Wolterink, T. Leiner, M.A. Viergever, I. Isgum

Dilated convolutional neural networks for cardiovascular MR segmentation in congenital heart disease Inproceedings

In: M.A. Zuluaga; K. Bhatia; B. Kainz; M.H. Moghari; D.F. Pace (Ed.): HVSMR 2016: MICCAI Workshop on Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease, pp. 95-102, Springer International Publishing, 2017.

Abstract | BibTeX


Abstracts

1.

J.M. Wolterink, A.M. Dinkla, M.H.F. Savenije, P.R. Seevinck, C.A.T. van den Berg, I. Isgum

MR-to-CT synthesis using cycle-consistent generative adversarial networks Abstract

In: 2017.

BibTeX

2.

R. van Hamersvelt, M. Zreik, N. Lessmann, J. Wolterink, M. Voskuil, M.A Viergever, T. Leiner, I. Isgum

Improving Specificity of Coronary CT Angiography for the Detection of Functionally Significant Coronary Artery Disease: A Deep Learning Approach Abstract

In: 2017.

Abstract | BibTeX

3.

N. Lessmann, B. van Ginneken, P.A. de Jong, W.B. Veldhuis, M.A. Viergever, I. Isgum

Deep learning analysis for automatic calcium scoring in routine chest CT Abstract

In: 2017.

Abstract | BibTeX

4.

B.D. de Vos, N. Lessmann, P.A. de Jong, M.A. Viergever, I. Isgum

Direct coronary artery calcium scoring in low-dose chest CT using deep learning analysis Abstract

In: 2017.

Abstract | BibTeX

5.

J.M. Wolterink, I. Isgum, M.A. Viergever, T. Leiner

Cardiovascular MR image segmentation in congenital heart disease using a dilated convolutional neural network Abstract

In: 2017.

BibTeX

6.

M. Zreik, N. Lessmann, R. van Hamersvelt, J. Wolterink, M. Voskuil, M.A Viergever, T. Leiner, I. Isgum

Deep learning analysis of the left ventricular myocardium in cardiac CT images enables detection of functionally significant coronary artery stenosis regardless of coronary anatomy Abstract

In: 2017.

Abstract | BibTeX

7.

J.M. Wolterink, T. Leiner, M.A. Viergever, I. Isgum

An adversarial deep learning approach to coronary CT radiation reduction Abstract

In: 2017.

Abstract | BibTeX

8.

A.M. den Harder, J.M. Wolterink, P.A. de Jong, M.C.H. de Groot, I. Isgum, W.B. Veldhuis, S. Haijtema, I.E. Hoefer, T. Leiner

Towards understanding the role of the hematological system in the pathophysiology of coronary calcifications: A cohort study Abstract

In: 2017.

BibTeX


PhD Theses

1.

J.M. Wolterink

Machine learning based analysis of cardiovascular images PhD Thesis

Utrecht University, The Netherlands, 2017, ISBN: 978-94-6299-587-1.

Abstract | BibTeX


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2016

Journal Articles

1.

S.A.M. Gernaat, I. Isgum, B.D. de Vos, R.A.P. Takx, D.A. Young Afat, N. Rijnberg, D.E. Grobbee, Y. van der Graaf, P.A. de Jong, T. Leiner, H.J.G.D. van den Bongard, J.P. Pignol, H.M. Verkooijen

Automatic coronary artery calcium scoring on radiotherapy planning CT scans of breast cancer patients: reproducibility and association with traditional cardiovascular risk factors Journal Article

Plos One, 11 (12), pp. e0167925, 2016.

Abstract | BibTeX

2.

P. Natarajan; J. C. Bis; L. F. Bielak; A. J. Cox; M. Dorr; M. F. Feitosa; N. Franceschini; X. Guo; S-J. Hwang; A. Isaacs; M. A. Jhun; et al

Multiethnic Exome-Wide Association Study of Subclinical Atherosclerosis Journal Article

Circulation. Cardiovascular genetics, 9 (6), pp. 511-520, 2016.

Abstract | BibTeX

3.

A.M. den Harder, J.M. Wolterink, M.J. Willemink, A.M.R. Schilham, P.A. de Jong, R.P.J. Budde, H.M. Nathoe, I. Isgum, T. Leiner

Submillisievert coronary calcium quantification using model-based iterative reconstruction: a within-patient analysis Journal Article

European Journal of Radiology, 85 (11), pp. 2152-2159, 2016.

Abstract | BibTeX

4.

S.W. van der Laan; T. Fall; A. Soumaré; A. Teumer; S. Sedaghat; J. Baumert; D. Zabaneh; J. van Setten; I. Isgum; T.E. Galesloot; J. Arpegård; P. Amouyel; S. Trompet; M. Waldenberger; M. Dörr; P.K. Magnusson; V. Giedraitis; A. Larsson; A.P. Morris; J.F. Felix; A.C. Morrison; N. Franceschini; J.C. Bis; M. Kavousi; C. O'Donnell; F. Drenos; V. Tragante; P.B. Munroe; R. Malik; M. Dichgans; et al

Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study Journal Article

Journal of the American College of Cardiology, 68 (9), pp. 934-945, 2016.

Abstract | BibTeX

5.

K.J. Kersbergen, F. Leroy, I. Isgum, F. Groenendaal, L.S. de Vries, N.H.P. Claessens, I.C. van Haastert, P. Moeskops, C. Fischer, J.-F. Mangin, M.A. Viergever, J. Dubois, M.J.N.L. Benders

Relation between clinical risk factors, early cortical changes, and neurodevelopmental outcome in preterm infants Journal Article

NeuroImage, 5 (142), pp. 301-310, 2016.

BibTeX

6.

N.H.P. Claessens, P. Moeskops, A. Buchmann, B. Latal, W. Knirsch, I. Scheer, I. Isgum, L.S. de Vries, M.J.N.L. Benders, M. von Rhein

Delayed cortical gray matter development in neonates with severe congenital heart disease Journal Article

Pediatric Research, 80 (5), pp. 668-674, 2016.

BibTeX

7.

J.M. Wolterink, T. Leiner, B.D. de Vos, R.W. van Hamersvelt, M.A. Viergever, I. Isgum

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks Journal Article

Medical Image Analysis, 34 , pp. 123-136, 2016.

Abstract | BibTeX

8.

P. Moeskops, M.A. Viergever, A.M. Mendrik, L.S. de Vries, M.J.N.L. Benders, I. Isgum

Automatic segmentation of MR brain images with a convolutional neural network Journal Article

IEEE Transactions on Medical Imaging, 35 (5), pp. 1252-1261, 2016.

Abstract | BibTeX

9.

P.M. Lemmers, M.J.N.L. Benders, R. D'Ascenzo, J. Zethof, T. Alderliesten, K.J. Kersbergen, I. Isgum, L.S. de Vries, F. Groenendaal, F. van Bel

Patent ductus arteriosus and brain volume. Journal Article

Pediatrics, 137 (4), pp. e2015309, 2016.

Abstract | BibTeX

10.

J.M. Wolterink, T. Leiner, B.D. de Vos, J-L. Coatrieux, B.M. Kelm, S. Kondo, R.A. Salgado, R. Shahzad, H. Shu, M. Snoeren, R.A.P. Takx, L.J. van Vliet, T. van Walsum, T.P. Willems, G. Yang, Y. Zheng, M.A. Viergever, I. Isgum

An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework Journal Article

Medical Physics, 43 (5), pp. 2361, 2016.

Abstract | BibTeX

11.

A. Vos, W. van Hecke, W.G.M. Spliet, R. Goldschmeding, I. Isgum, R. Kockelkoren, R.L.A.W. Bleys, W.P.T.M. Mali, P.A. de Jong, A. Vink

Predominance of nonatherosclerotic internal elastic lamina calcification in the intracranial internal carotid artery Journal Article

Stroke, 47 (1), pp. 221-3, 2016.

Abstract | BibTeX

12.

M.J. Brouwer, L.S. de Vries, K.J. Kersbergen, N.E. van der Aa, A.J. Brouwer, M.A. Viergever, I. Isgum, K.S. Han, F. Groenendaal, M.J.N.L. Benders

Effects of posthemorrhagic ventricular dilatation in the preterm infant on brain volumes and white matter diffusion variables at term-equivalent age Journal Article

Journal of Pediatrics, 168 , pp. 41-49.e1, 2016.

Abstract | BibTeX


Inproceedings

1.

P. Moeskops, J.M. Wolterink, B.H.M. van der Velden, K.G.A. Gilhuijs, T. Leiner, M.A. Viergever, I. Isgum

Deep learning for multi-task medical image segmentation in multiple modalities Inproceedings

In: Medical Image Computing and Computer-Assisted Intervention, pp. 478-486, 2016.

Abstract | BibTeX

2.

B.D. de Vos, M.A. Viergever, P.A. de Jong, I. Isgum

Automatic Slice Identification in 3D Medical Images with a ConvNet Regressor Inproceedings

In: Deep Learning and Data Labeling for Medical Applications: First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, MICCAI 2016, Athens, Greece, pp. 161–169, 2016.

Abstract | BibTeX

3.

N. Lessmann, I. Isgum, A.A.A. Setio, B.D. de Vos, F. Ciompi, P.A. de Jong, M. Oudkerk, W.P.Th.M. Mali, M.A. Viergever, B. van Ginneken

Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT Inproceedings

In: SPIE Medical Imaging, pp. 978511, 2016, (Bla).

Abstract | Links | BibTeX

4.

I. Isgum, B.D. de Vos, J.M. Wolterink, D. Dey, D.S. Berman, M. Rubeaux, T. Leiner, P.J. Slomka

Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs Inproceedings

In: SPIE Medical Imaging, pp. 978405-1-978405-6, 2016.

Abstract | BibTeX

5.

B.D. de Vos, J.M. Wolterink, P.A. de Jong, M.A. Viergever, I. Isgum

2D image classification for 3D anatomy localization; employing deep convolutional neural networks Inproceedings

In: SPIE Medical Imaging, pp. 97841Y-1-97841Y-7, 2016.

Abstract | BibTeX

6.

B.D. de Vos, J. van Setten, P.A. de Jong, W.P. Mali, M. Oudkerk, M.A. Viergever, I. Isgum

Genome-Wide Association Study of Coronary and Aortic Calcification in Lung Cancer Screening CT Inproceedings

In: SPIE Medical Imaging, pp. 97841L-1-97841L-6, 2016.

Abstract | BibTeX

7.

M. Zreik; T. Leiner; B.D. de Vos; R.W. van Hamersvelt; M.A. Viergever; I. Isgum

Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks Inproceedings

In: IEEE International Symposium on Biomedical Imaging, pp. pp. 40-43, 2016.

BibTeX


Abstracts

1.

F. Mohamed Hoesein, E. Pompe, D.A. Lynch, N. Lessmann, J.W.J. Lammers, I. Isgum, P.A. de Jong

Computed tomographic findings are associated with respiratory mortality in the National Lung Screening Trial Abstract

In: 2016.

Abstract | BibTeX

2.

A.M. den Harder; J.M. Wolterink; M.J. Willemink; A.M.R. Schilham; P.A. de Jong; R.P.J. Budde; H.M. Nathoe; I. Isgum; T. Leiner

Low-dose coronary calcium scoring with model-based iterative reconstruction Abstract

In: 2016.

BibTeX


PhD Theses

1.

P. Moeskops

Automatic MRI-based quantification of brain characteristics in preterm newborns PhD Thesis

Utrecht University, The Netherlands, 2016, ISBN: 978-90-393-6625-7.

Abstract | BibTeX


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2015

Journal Articles

1.

K. Keunen, I. Isgum, B. van Kooij, P. Anbeek, I. van Haastert, C. Koopman-Esseboom, P. Fieret-van Stam, R.A. Nievelstein, M.A. Viergever, L. de Vries, G. Groenendaal, M. Benders

Brain volumes at term-equivalent age in preterm infants: imaging biomarkers for neurodevelopmental outcome through early school age Journal Article

The journal of Pediatrics, 172 , pp. 88-95, 2015.

Abstract | BibTeX

2.

P. Moeskops; M.J.N.L. Benders; K.J. Kersbergen; F. Groenendaal; L.S. de Vries; M.A. Viergever; I. Išgum

Development of cortical morphology evaluated with longitudinal MR brain images of preterm infants Journal Article

PLOS ONE, 10 (7), pp. e0131552, 2015.

Abstract | BibTeX

3.

P. Moeskops, M.J.N.L. Benders, S.M. Chita, K.J. Kersbergen, F. Groenendaal, L.S. de Vries, M.A. Viergever, I. Išgum

Automatic segmentation of MR brain images of preterm infants using supervised classification Journal Article

NeuroImage, 118 , pp. 628-641, 2015.

Abstract | BibTeX

4.

M.J. Willemink, R.A. Takx, I. Išgum, H.J. de Koning, M. Oudkerk, W.P. Mali, R.P. Budde, T. Leiner, R. Vliegenthart, P.A. de Jong

Prognostic value of heart valve calcifications for cardiovascular events in a lung cancer screening population Journal Article

The International Journal of Cardiovascular Imaging, 31 (6), pp. 1243-1249, 2015.

Abstract | BibTeX

5.

P.M. Jairam, P.A. de Jong, W.P. Mali, I. Isgum, Y. van der Graaf; PROVIDI study-group.

Cardiovascular disease prediction: do pulmonary disease-related chest CT features have added value? Journal Article

European Radiology, 25 (6), pp. 1646-1654, 2015.

Abstract | BibTeX

6.

J.M. Wolterink, T. Leiner, R.A.P. Takx, M.A. Viergever; I. Isgum

Automatic coronary calcium scoring in non-contrast-enhanced ECG-triggered cardiac CT with ambiguity detection Journal Article

IEEE Transactions on Medical Imaging, 34 (9), pp. 1867-1878, 2015.

Abstract | BibTeX

7.

J. van Setten; I. Isgum; S. Pechlivanis; V. Tragante; P.A. de Jong; J. Smolonska; M. Platteel; P. Hoffmann; M. Oudkerk; H.J. de Koning; M.M. Nöthen; S. Moebus; R. Erbel; K.H. Jöckel; M.A. Viergever; W.P. Mali; P.I. de Bakker

Serum lipid levels, body mass index, and their role in coronary artery calcification: A polygenic analysis Journal Article

Circulation: Cardiovascular Genetics, 8 (2), pp. 327-333, 2015.

Abstract | BibTeX

8.

R.A.P. Takx; I. Isgum; M.J. Willemink; Y. van der Graaf; H.J. de Koning; R. Vliegenthart; M. Oudkerk; T. Leiner; P.A. de Jong

Quantification of coronary artery calcium in non-gated CT to predict cardiovascular events in male lung cancer screening participants: Results of the NELSON Study Journal Article

Journal of Cardiovascular Computed Tomography, 9 (1), pp. 50-57, 2015.

Abstract | BibTeX

9.

R.A. Takx; R. Vliegenthart; F.A. Hoesein; I. Isgum; H.J. de Koning; W.P. Mali; C.M. van der Aalst; P. Zanen; J.W. Lammers; H.J. Groen; E.M. van Rikxoort; M. Schmidt; B. van Ginneken; M. Oudkerk; T. Leiner; P.A. de Jong

Pulmonary function and CT biomarkers as risk factors for cardiovascular events in male lung cancer screening participants: the NELSON study Journal Article

European Radiology, 25 (1), pp. 65-71, 2015.

Abstract | BibTeX

10.

C.F. Buckens; Y. van der Graaf; H.M. Verkooijen; W.P. Mali; I. Isgum; C.P. Mol; H.J. Verhaar; R. Vliegenthart; M. Oudkerk; C.M. van Aalst; H.J. de Koning; P.A. de Jong

Osteoporosis markers on low-dose lung cancer screening chest computed tomography scans predict all-cause mortality Journal Article

European Radiology, 25 (1), pp. 132-139, 2015.

Abstract | BibTeX

11.

I. Isgum, M.J.N.L. Benders, B. Avants, M.J. Cardoso, S.J. Counsell, E. Fischi Gomez, L. Gui, P. S Hüppi, K.J. Kersbergen, A. Makropoulos, A. Melbourne, P. Moeskops, C.P. Mol, M. Kuklisova-Murgasova, D. Rueckert, J.A. Schnabel, V. Srhoj-Egekher, J. Wu, S. Wang, L.S. de Vries, M.A. Viergever

Evaluation of automatic neonatal brain segmentation algorithms: the NeoBrainS12 challenge Journal Article

Medical Image Analysis, 20 (1), pp. 135-151, 2015.

Abstract | BibTeX


Inproceedings

1.

K. Murphy, N E. van der Aa, S. Negro, F. Groenendaal, L.S. de Vries, M.A. Viergever, M.J.N.L. Benders, I. Isgum

Automatic segmentation of cerebral ischemic lesions in neonatal apparent diffusion coefficient maps Inproceedings

In: Brain Lesions (Brainles) workshop in conjuction with International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2015.

BibTeX

2.

J.M. Wolterink, T. Leiner, M.A. Viergever, I. Isgum

Automatic coronary calcium scoring in cardiac CT angiography using convolutional neural networks Inproceedings

In: N. Navab, J. Hornegger, W.M. Wells, A.F. Frangi (Ed.): Medical Image Computing and Computer-Assisted Intervention, pp. 589-596, Springer International Publishing, 2015.

Abstract | BibTeX

3.

B.D. de Vos; P.A. de Jong; J.M. Wolterink; R. Vliegenthart; G.V.F. Wielingen; M.A. Viergever; I. Isgum

Automatic machine learning based prediction of cardiovascular events in lung cancer screening data Inproceedings

In: SPIE Medical Imaging, pp. 94140D, 2015.

Abstract | BibTeX

4.

P. Moeskops; M.A. Viergever; M.J.N.L. Benders; I. Isgum

Evaluation of an automatic brain segmentation method developed for neonates on adult MR brain images Inproceedings

In: SPIE Medical Imaging, pp. 941315, 2015.

Abstract | BibTeX


Abstracts

1.

J. Šprem, B.D. de Vos, R. Vliegenthart, M.A. Viergever, P. A. de Jong, I. Isgum

Increasing the Interscan Reproducibility of Coronary Calcium Scoring by Partial Volume Correction in Low-Dose non-ECG Synchronized CT: Phantom Study Abstract

In: 2015.

BibTeX

2.

N. Lessmann, I. Isgum, S. Lam, J. Mayo, P.A. de Jong, M.A. Viergever, B. van Ginneken

Automatic coronary calcium scoring and cardiovascular risk estimation in the Pan-Canadian lung cancer screening trial Abstract

In: 2015.

Abstract | BibTeX

3.

P. Moeskops, N.C. A'Campo, M.J.N.L. Benders, L.S. de Vries, M.A. Viergever, I. Isgum

Automatic whole brain segmentation of MR brain images of preterm infants and adults using supervised classification Abstract

In: 2015.

BibTeX

4.

J.M. Wolterink; T. Leiner; M.J. Willemink; M.A. Viergever; I. Isgum

The impact of iterative reconstruction on detectability and quantification of calcifications in CT coronary calcium Scoring: Individual lesion-by-lesion comparison Abstract

In: 2015.

Abstract | BibTeX


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2014

Journal Articles

1.

C.A. Blok; K.J. Kersbergen; N.E. van der Aa; B.J. van Kooij; P. Anbeek; I. Isgum; L.S. de Vries; T.G. Krediet; F. Groenendaal; H.J. Vreman; F. van Bel; M.J. Benders

Unmyelinated white matter loss in the preterm brain is associated with early increased levels of end-tidal carbon monoxide Journal Article

PLoS One, 9 (3), pp. e89061, 2014.

Abstract | BibTeX

2.

R.A.P. Takx; P.A. de Jong; T. Leiner; M. Oudkerk; H.J. de Koning; C.P. Mol; M.A. Viergever; I. Isgum

Automated coronary artery calcification scoring in non-gated chest CT: Agreement and reliability Journal Article

PLoS One, 9 (3), pp. e91239, 2014.

Abstract | BibTeX

3.

M.J.N.L. Benders; N.E. van der Aa; M. Rok; H.L. van Straaten; I. Isgum; M.A. Viergever; F. Groenendaal; L.S. de Vries; F. van Bel

Feasibility and safety of erythropoietin for neuroprotection after perinatal arterial ischemic stroke Journal Article

The Journal of Pediatrics, 64 (3), pp. 481-486.e2, 2014.

Abstract |