Publications
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Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis
Zreik, Majd, Hampe, Nils, Leiner, Tim, Khalili, Nadih, Wolterink, Jelmer M., Voskuil, Michiel, Viergever, Max A., Išgum, Ivana
2021 in Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis: Medical Imaging 2021 p. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 11596)
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Deep learning analysis of coronary arteries in cardiac CT angiography for detection of patients requiring invasive coronary angiography
Zreik, Majd, van Hamersvelt, Robbert W, Khalili, Nadieh, Wolterink, Jelmer M, Voskuil, Michiel, Viergever, Max A, Leiner, Tim, Isgum, Ivana
May
2020
in
IEEE Transactions on Medical Imaging
39
(5),
p. 1545-1557
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A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography
Zreik, Majd, van Hamersvelt, Robbert W, Wolterink, Jelmer M, Leiner, Tim, Viergever, Max A, Isgum, Ivana
Jul
2019
in
IEEE Transactions on Medical Imaging
38
(7),
p. 1588-1598
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Deep learning analysis of left ventricular myocardium in CT angiographic intermediate-degree coronary stenosis improves the diagnostic accuracy for identification of functionally significant stenosis
van Hamersvelt, Robbert W., Zreik, Majd, Voskuil, Michiel, Viergever, Max A., Išgum, Ivana, Leiner, Tim
May
2019
in
European Radiology
29
(5),
p. 2350-2359
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Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning
Van Velzen, Sanne G.M., Zreik, Majd, Lessmann, Nikolas, Viergever, Max A., De Jong, Pim A., Verkooijen, Helena M., Išgum, Ivana
jan
2019 in Direct prediction of cardiovascular mortality from low-dose chest CT using deep learning: Medical Imaging 2019 p. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10949)
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Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI
Khalili, N., Turk, E., Zreik, M., Viergever, M. A., Benders, M. J.N.L., Išgum, I.
jan
2019 in Generative Adversarial Network for Segmentation of Motion Affected Neonatal Brain MRI: Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings p. 320-328 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11766 LNCS)
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Improving myocardium segmentation in cardiac CT angiography using spectral information
Bruns, Steffen, Wolterink, Jelmer M., Van Hamersvelt, Robbert W., Zreik, Majd, Leiner, Tim, Išgum, Ivana
jan
2019 in Improving myocardium segmentation in cardiac CT angiography using spectral information: Medical Imaging 2019 p. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10949)
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Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions
Lessmann, Nikolas, van Ginneken, Bram, Zreik, M, de Jong, Pim A., de Vos, Bob D., Viergever, Max A., Isgum, Ivana
Feb
2018
in
IEEE Transactions on Medical Imaging
37
(2),
p. 615-625
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Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis
Zreik, Majd, Lessmann, Nikolas, van Hamersvelt, Robbert W., Wolterink, Jelmer M., Voskuil, Michiel, Viergever, Max A., Leiner, Tim, Išgum, Ivana
Feb
2018
in
Medical Image Analysis
44
p. 72-85
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Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks
Zreik, M, Leiner, Tim, De Vos, Bob D., Van Hamersvelt, Robbert W., Viergever, Max A., Isgum, Ivana
jun
2016 in Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks: 2016 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2016 - Proceedings p. 40-43 (Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging ; vol. 2016 - June)