Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Bruns, Steffen"'
Autor:
van Herten, Rudolf L. M., Lagogiannis, Ioannis, Wolterink, Jelmer M., Bruns, Steffen, Meulendijks, Eva R., Dey, Damini, de Groot, Joris R., Henriques, José P., Planken, R. Nils, Saitta, Simone, Išgum, Ivana
Deep learning-based medical image segmentation and surface mesh generation typically involve a sequential pipeline from image to segmentation to meshes, often requiring large training datasets while making limited use of prior geometric knowledge. Th
Externí odkaz:
http://arxiv.org/abs/2409.11837
Autor:
Bruns, Steffen, Wolterink, Jelmer M., Takx, Richard A. P., van Hamersvelt, Robbert W., Suchá, Dominika, Viergever, Max A., Leiner, Tim, Išgum, Ivana
Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic extraction of these measures in patients undergoing only non-contrast-
Externí odkaz:
http://arxiv.org/abs/2008.03985
Autor:
Sander, Jörg, de Vos, Bob D., Bruns, Steffen, Planken, Nils, Viergever, Max A., Leiner, Tim, Išgum, Ivana
Publikováno v:
In Computers in Biology and Medicine September 2023 164
CNN-Based Segmentation of the Cardiac Chambers and Great Vessels in Non-Contrast-Enhanced Cardiac CT
Quantification of cardiac structures in non-contrast CT (NCCT) could improve cardiovascular risk stratification. However, setting a manual reference to train a fully convolutional network (FCN) for automatic segmentation of NCCT images is hardly feas
Externí odkaz:
http://arxiv.org/abs/1908.07727
Autor:
Bruns, Steffen, Wolterink, Jelmer M., van Hamersvelt, Robbert W., Zreik, Majd, Leiner, Tim, Išgum, Ivana
Accurate segmentation of the left ventricle myocardium in cardiac CT angiography (CCTA) is essential for e.g. the assessment of myocardial perfusion. Automatic deep learning methods for segmentation in CCTA might suffer from differences in contrast-a
Externí odkaz:
http://arxiv.org/abs/1810.03968
Autor:
Bruns, Steffen, Wolterink, Jelmer M., van den Boogert, Thomas P.W., Runge, Jurgen H., Bouma, Berto J., Henriques, José P., Baan, Jan, Viergever, Max A., Planken, R. Nils, Išgum, Ivana
Publikováno v:
In Computers in Biology and Medicine March 2022 142
Autor:
van Velzen, Sanne G.M., Bruns, Steffen, Wolterink, Jelmer M., Leiner, Tim, Viergever, Max A. *, Verkooijen, Helena M., Išgum, Ivana
Publikováno v:
In International Journal of Radiation Oncology, Biology, Physics 1 March 2022 112(3):611-620
Akademický článek
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Autor:
Bruns, Steffen, Wolterink, Jelmer M., Van Den Boogert, Thomas P. W., Henriques, José P., Baan, Jan, Planken, R. Nils, Išgum, Ivana, Landman, Bennett A., Isgum, Ivana
Publikováno v:
Medical Imaging 2021: Image Processing
Medical Imaging 2021
Medical Imaging 2021: Image Processing: 15-19 February 2021, online only, Unitred States, 1
Medical Imaging 2021: Image Processing, 11596
Medical Imaging 2021
Medical Imaging 2021: Image Processing: 15-19 February 2021, online only, Unitred States, 1
Medical Imaging 2021: Image Processing, 11596
4D cardiac CT angiography (CCTA) images acquired for transcatheter aortic valve implantation (TAVI) planning provide a wealth of information about the morphology of the heart throughout the cardiac cycle. We propose a deep learning method to automati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0c9bd7476ac2fc8dfa27425e0849c185
https://doi.org/10.1117/12.2581020
https://doi.org/10.1117/12.2581020
Autor:
Meulendijks, Eva R., Fabrizi, Benedetta, Bruns, Steffen, Boogert, Thomas vd, Wesselink, Robin, Boven, Wim Jan van, Driessen, Antoine, Niessen, Hans, de Vries, Tim A.C., Eringa, Ed, Planken, Nils, Isgum, Ivana, Dey, Damini, Krul, Sebastien P., Hoebe, Ron, de Groot, Joris R., Al-Shama, Rushd
Publikováno v:
In Heart Rhythm May 2023 20(5) Supplement:S270-S271