Zobrazeno 1 - 10 of 10 006 pro vyhledávání: '"Hornegger, J"'
1
Akademický článek
Respiratory motion compensation by model-based catheter tracking during EP procedures
Autor: Brost, A. a, ⁎, Liao, R. b, Strobel, N. c, Hornegger, J. a, d
Publikováno v: In Medical Image Analysis 2010 14(5):695-706
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2
Akademický článek
Interventional 4D motion estimation and reconstruction of cardiac vasculature without motion periodicity assumption
Autor: Rohkohl, C. a, b, ⁎, Lauritsch, G. b, Biller, L. c, b, Prümmer, M. a, Boese, J. b, Hornegger, J. a, d
Publikováno v: In Medical Image Analysis 2010 14(5):687-694
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3
Akademický článek
Discrete tomography by convex–concave regularization and D.C. programming
Autor: Schüle, T. a, c, Schnörr, C. a, Weber, S. a, Hornegger, J. b
Publikováno v: In Discrete Applied Mathematics 2005 151(1):229-243
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4
Akademický článek
A Linear Programming Relaxation for Binary Tomography with Smoothness Priors
Autor: Weber, S. a, ∗, Schnorr, C. a, Hornegger, J. b
Publikováno v: In Electronic Notes in Discrete Mathematics 2003 12:243-254
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5
Classification with Truncated l1 Distance Kernel
Autor: Huang, X, Suykens, Johan, Wang, S, Maier, A, Hornegger, J
This brief proposes a truncated distance (TL1) kernel, which results in a classifier that is nonlinear in the global region but is linear in each subregion. With this kernel, the subregion structure can be trained using all the training data and loca
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1131::377d4ee551a250929aaa18fd2f85fb8a
https://lirias.kuleuven.be/handle/123456789/633241
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6
Crossing-preserving multi-scale vesselness
Autor: Hannink, J., Duits, R., Bekkers, E.J., Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R.
Publikováno v: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 ISBN: 9783319104690
MICCAI (2)
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 (17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II), 603-610
STARTPAGE=603;ENDPAGE=610;TITLE=Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014 (17th International Conference, Boston, MA, USA, September 14-18, 2014, Proceedings, Part II)
The multi–scale Frangi vesselness filter is an established tool in (retinal) vascular imaging. However, it cannot properly cope with crossings or bifurcations since it only looks for elongated structures. Therefore, we disentangle crossings/bifurca
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c2ff940d7dd246000ceb001d21fc2a98
https://doi.org/10.1007/978-3-319-10470-6_75
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7
Akademický článek
Generation of deep learning based virtual non-contrast CT using dual-layer dual-energy CT and its application to planning CT for radiotherapy.
Autor: Kim, Jungye1 (AUTHOR), Lee, Jimin2,3 (AUTHOR), Kim, Bitbyeol4 (AUTHOR), Kim, Sangwook5 (AUTHOR), Jin, Hyeongmin4 (AUTHOR), Jung, Seongmoon4,6 (AUTHOR) smjung@kriss.re.kr
Publikováno v: PLoS ONE. 12/30/2024, Vol. 19 Issue 12, p1-20. 20p.
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8
Akademický článek
SHIVA-CMB: a deep-learning-based robust cerebral microbleed segmentation tool trained on multi-source T2*GRE- and susceptibility-weighted MRI.
Autor: Tsuchida, Ami1,2 (AUTHOR), Goubet, Martin3 (AUTHOR), Boutinaud, Philippe4 (AUTHOR), Astafeva, Iana1,2 (AUTHOR), Nozais, Victor4 (AUTHOR), Hervé, Pierre-Yves4 (AUTHOR), Tourdias, Thomas5,6 (AUTHOR), Debette, Stéphanie2 (AUTHOR), Joliot, Marc1 (AUTHOR) marc.joliot@u-bordeaux.fr
Publikováno v: Scientific Reports. 12/28/2024, Vol. 14 Issue 1, p1-16. 16p.
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9
Akademický článek
Deep learning for opportunistic, end-to-end automated assessment of epicardial adipose tissue in pre-interventional, ECG-gated spiral computed tomography.
Autor: Theis, Maike1 (AUTHOR) maike.theis@ukbonn.de, Garajová, Laura1 (AUTHOR), Salam, Babak1 (AUTHOR), Nowak, Sebastian1 (AUTHOR), Block, Wolfgang1,2,3 (AUTHOR), Attenberger, Ulrike I.1 (AUTHOR), Kütting, Daniel1 (AUTHOR), Luetkens, Julian A.1 (AUTHOR), Sprinkart, Alois M.1 (AUTHOR)
Publikováno v: Insights into Imaging. 12/19/2024, Vol. 15 Issue 1, p1-11. 11p.
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10
Akademický článek
Single‐Step Sampling Approach for Unsupervised Anomaly Detection of Brain MRI Using Denoising Diffusion Models.
Autor: Damudi, Mohammed Z.1 (AUTHOR), Kini, Anita S.1 (AUTHOR) anita.kini@manipal.edu, Abu-Qasmieh, Isam1 (AUTHOR) iabuqasmieh@yu.edu.jo
Publikováno v: International Journal of Biomedical Imaging. 12/19/2024, Vol. 2024, p1-15. 15p.
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