Zobrazeno 1 - 10
of 101
pro vyhledávání: '"Laura M. Schreiber"'
Autor:
Alena Kollmann, David Lohr, Markus J. Ankenbrand, Maya Bille, Maxim Terekhov, Michael Hock, Ibrahim Elabyad, Steffen Baltes, Theresa Reiter, Florian Schnitter, Wolfgang R. Bauer, Ulrich Hofmann, Laura M. Schreiber
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract Cardiac magnetic resonance (CMR) imaging allows precise non-invasive quantification of cardiac function. It requires reliable image segmentation for myocardial tissue. Clinically used software usually offers automatic approaches for this ste
Externí odkaz:
https://doaj.org/article/bcf38e5e496f4182ba99254e92a54efa
Autor:
Laura M. Schreiber, David Lohr, Steffen Baltes, Ulrich Vogel, Ibrahim A. Elabyad, Maya Bille, Theresa Reiter, Aleksander Kosmala, Tobias Gassenmaier, Maria R. Stefanescu, Alena Kollmann, Julia Aures, Florian Schnitter, Mihaela Pali, Yuichiro Ueda, Tatiana Williams, Martin Christa, Ulrich Hofmann, Wolfgang Bauer, Brenda Gerull, Alma Zernecke, Süleyman Ergün, Maxim Terekhov
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 10 (2023)
A key step in translational cardiovascular research is the use of large animal models to better understand normal and abnormal physiology, to test drugs or interventions, or to perform studies which would be considered unethical in human subjects. Ul
Externí odkaz:
https://doaj.org/article/9193eef9bf9242b49f87492d8e2116d8
Autor:
David Lohr, Arne Thiele, Max Stahnke, Vera Braun, Elia Smeir, Joachim Spranger, Sebastian Brachs, Robert Klopfleisch, Anna Foryst-Ludwig, Laura M. Schreiber, Ulrich Kintscher, Niklas Beyhoff
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 9 (2022)
BackgroundObesity exerts multiple deleterious effects on the heart that may ultimately lead to cardiac failure. This study sought to characterize myocardial microstructure and function in an experimental model of obesity-related cardiac dysfunction.M
Externí odkaz:
https://doaj.org/article/f61a6287ebfa4d6b852632693ca330ce
Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI
Publikováno v:
BMC Medical Imaging, Vol 21, Iss 1, Pp 1-8 (2021)
Abstract Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance
Externí odkaz:
https://doaj.org/article/23381947d8204aba948bbdc4368e2359
Autor:
Niklas Beyhoff, David Lohr, Arne Thiele, Anna Foryst-Ludwig, Robert Klopfleisch, Laura M. Schreiber, Ulrich Kintscher
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 7 (2020)
Although heart failure following myocardial infarction (MI) represents a major health burden, underlying microstructural and functional changes remain incompletely understood. Here, we report on a case of unexpected MI after treatment with the catech
Externí odkaz:
https://doaj.org/article/08735a29d5854e3d90626672ae447d50
Publikováno v:
Magnetic Resonance Materials in Physics, Biology and Medicine. 36:279-293
Introduction MRI of excised hearts at ultra-high field strengths ($${\mathrm{B}}_{0}$$ B 0 ≥7 T) can provide high-resolution, high-fidelity ground truth data for biomedical studies, imaging science, and artificial intelligence. In this study, we de
Autor:
Lei Li, Fuping Wu, Sihan Wang, Xinzhe Luo, Carlos Martín-Isla, Shuwei Zhai, Jianpeng Zhang, Yanfei Liu, Zhen Zhang, Markus J. Ankenbrand, Haochuan Jiang, Xiaoran Zhang, Linhong Wang, Tewodros Weldebirhan Arega, Elif Altunok, Zhou Zhao, Feiyan Li, Jun Ma, Xiaoping Yang, Elodie Puybareau, Ilkay Oksuz, Stephanie Bricq, Weisheng Li, Kumaradevan Punithakumar, Sotirios A. Tsaftaris, Laura M. Schreiber, Mingjing Yang, Guocai Liu, Yong Xia, Guotai Wang, Sergio Escalera, Xiahai Zhuang
Publikováno v:
Li, L, Wu, F, Wang, S, Luo, X, Martin-Isla, C, Zhai, S, Zhang, J, Liu7, Y, Zhang, Z, Ankenbrand, M J, Jiang, H, Zhang, X, Wang, L, Arega, T W, Altunok, E, Zhao, Z, Li, F, Ma, J, Yang, X, Puybareau, E, Oksuz, I, Bricq, S, Li, W, Punithakumar, K, Tsaftaris, S A, Schreiber, L M, Yang, M, Liu, G, Xia, Y, Wang, G, Escalera, S & Zhuang, X 2023, ' MyoPS A Benchmark of Myocardial Pathology Segmentation Combining Three-Sequence Cardiac Magnetic Resonance Images ', Medical Image Analysis, vol. 87, 102808 . https://doi.org/10.1016/j.media.2023.102808
Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment. This work defines a new task of medic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e8087d7c379175b72701f28fa025e11
https://www.pure.ed.ac.uk/ws/files/341860919/2201.03186v1.pdf
https://www.pure.ed.ac.uk/ws/files/341860919/2201.03186v1.pdf
Publikováno v:
IEEE Transactions on Microwave Theory and Techniques. 69:3540-3557
Two 16-element radio frequency (RF) transceiver antisymmetric coil arrays with two different implementation designs aiming for improved characteristics for static phase $B_{1}^{+}$ shimming and parallel receive were developed for human cardiac MRI at
Autor:
Irvin Teh, William A. Romero R., Jordan Boyle, Jaume Coll‐Font, Erica Dall'Armellina, Daniel B. Ennis, Pedro F. Ferreira, Prateek Kalra, Arunark Kolipaka, Sebastian Kozerke, David Lohr, François‐Pierre Mongeon, Kévin Moulin, Christopher Nguyen, Sonia Nielles‐Vallespin, Brian Raterman, Laura M. Schreiber, Andrew D. Scott, David E. Sosnovik, Christian T. Stoeck, Cyril Tous, Elizabeth M. Tunnicliffe, Andreas M. Weng, Pierre Croisille, Magalie Viallon, Jürgen E. Schneider
Publikováno v:
NMR in Biomedicine
NMR in Biomedicine, In press, ⟨10.1002/nbm.4685⟩
NMR in Biomedicine, In press, ⟨10.1002/nbm.4685⟩
International audience; Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30a248da9dc9ff3181d4f6ccb99f828f
Autor:
Wiebke Schlötelburg, Theresa Reiter, Markus J. Ankenbrand, Laura M. Schreiber, David Lohr, Tobias Wech
Publikováno v:
Magnetic Resonance in Medicine. 86:2179-2191
Purpose Artificial neural networks show promising performance in automatic segmentation of cardiac MRI. However, training requires large amounts of annotated data and generalization to different vendors, field strengths, sequence parameters, and path