Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Koen van Leemput"'
Autor:
Jelle Praet, Lina Anderhalten, Giancarlo Comi, Dana Horakova, Tjalf Ziemssen, Patrick Vermersch, Carsten Lukas, Koen van Leemput, Marjan Steppe, Cristina Aguilera, Ella Maria Kadas, Alexis Bertrand, Jean van Rampelbergh, Erik de Boer, Vera Zingler, Dirk Smeets, Annemie Ribbens, Friedemann Paul
Publikováno v:
Frontiers in Immunology, Vol 15 (2024)
Multiple sclerosis (MS) is a devastating immune-mediated disorder of the central nervous system resulting in progressive disability accumulation. As there is no cure available yet for MS, the primary therapeutic objective is to reduce relapses and to
Externí odkaz:
https://doaj.org/article/80b9b6d1dce24d1e8a507b6f0114ba9f
Autor:
Harshvardhan Gazula, Henry FJ Tregidgo, Benjamin Billot, Yael Balbastre, Jonathan Williams-Ramirez, Rogeny Herisse, Lucas J Deden-Binder, Adria Casamitjana, Erica J Melief, Caitlin S Latimer, Mitchell D Kilgore, Mark Montine, Eleanor Robinson, Emily Blackburn, Michael S Marshall, Theresa R Connors, Derek H Oakley, Matthew P Frosch, Sean I Young, Koen Van Leemput, Adrian V Dalca, Bruce Fischl, Christine L MacDonald, C Dirk Keene, Bradley T Hyman, Juan E Iglesias
Publikováno v:
eLife, Vol 12 (2024)
We present open-source tools for three-dimensional (3D) analysis of photographs of dissected slices of human brains, which are routinely acquired in brain banks but seldom used for quantitative analysis. Our tools can: (1) 3D reconstruct a volume fro
Externí odkaz:
https://doaj.org/article/bee5031ed3ac4569bd31db0c5630fc96
Autor:
Sveinn Pálsson, Stefano Cerri, Hans Skovgaard Poulsen, Thomas Urup, Ian Law, Koen Van Leemput
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Survival prediction models can potentially be used to guide treatment of glioblastoma patients. However, currently available MR imaging biomarkers holding prognostic information are often challenging to interpret, have difficulties generaliz
Externí odkaz:
https://doaj.org/article/4ba34c5acbba48efa1f35eb357a11234
Autor:
Henry F.J. Tregidgo, Sonja Soskic, Juri Althonayan, Chiara Maffei, Koen Van Leemput, Polina Golland, Ricardo Insausti, Garikoitz Lerma-Usabiaga, César Caballero-Gaudes, Pedro M. Paz-Alonso, Anastasia Yendiki, Daniel C. Alexander, Martina Bocchetta, Jonathan D. Rohrer, Juan Eugenio Iglesias
Publikováno v:
NeuroImage, Vol 274, Iss , Pp 120129- (2023)
The human thalamus is a highly connected brain structure, which is key for the control of numerous functions and is involved in several neurological disorders. Recently, neuroimaging studies have increasingly focused on the volume and connectivity of
Externí odkaz:
https://doaj.org/article/41ba02e587244e2fb4a5199de07c8f03
Autor:
Stefano Cerri, Douglas N. Greve, Andrew Hoopes, Henrik Lundell, Hartwig R. Siebner, Mark Mühlau, Koen Van Leemput
Publikováno v:
NeuroImage: Clinical, Vol 38, Iss , Pp 103354- (2023)
In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that can handle multi-contrast data and robustly analyze images with white
Externí odkaz:
https://doaj.org/article/05edfde12cef469fb7f1e6bf5d8c9139
Publikováno v:
Physics and Imaging in Radiation Oncology, Vol 18, Iss , Pp 55-60 (2021)
Background and purpose: Radiotherapy (RT) based on magentic resonance imaging (MRI) only is currently used clinically in the pelvis. A synthetic computed tomography (sCT) is needed for dose planning. Here, we investigate the accuracy of cone beam CT
Externí odkaz:
https://doaj.org/article/a677f5e663d94cd1921fb106cc2f5635
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
Externí odkaz:
https://doaj.org/article/55a8215d54ad4b279eaba07f814f5557
Autor:
Donatas Sederevičius, Didac Vidal-Piñeiro, Øystein Sørensen, Koen van Leemput, Juan Eugenio Iglesias, Adrian V. Dalca, Douglas N. Greve, Bruce Fischl, Atle Bjørnerud, Kristine B. Walhovd, Anders M. Fjell
Publikováno v:
NeuroImage, Vol 237, Iss , Pp 118113- (2021)
Accurate and reliable whole-brain segmentation is critical to longitudinal neuroimaging studies. We undertake a comparative analysis of two subcortical segmentation methods, Automatic Segmentation (ASEG) and Sequence Adaptive Multimodal Segmentation
Externí odkaz:
https://doaj.org/article/1b05cac46e1e4f39afe9d8fec81caa6e
Autor:
Maria Ines Meyer, Ezequiel de la Rosa, Nuno Pedrosa de Barros, Roberto Paolella, Koen Van Leemput, Diana M. Sima
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
Most data-driven methods are very susceptible to data variability. This problem is particularly apparent when applying Deep Learning (DL) to brain Magnetic Resonance Imaging (MRI), where intensities and contrasts vary due to acquisition protocol, sca
Externí odkaz:
https://doaj.org/article/5f0d2a26ae5f4c04804acaa7faed7b04
Autor:
Stefano Cerri, Oula Puonti, Dominik S. Meier, Jens Wuerfel, Mark Mühlau, Hartwig R. Siebner, Koen Van Leemput
Publikováno v:
NeuroImage, Vol 225, Iss , Pp 117471- (2021)
Here we present a method for the simultaneous segmentation of white matter lesions and normal-appearing neuroanatomical structures from multi-contrast brain MRI scans of multiple sclerosis patients. The method integrates a novel model for white matte
Externí odkaz:
https://doaj.org/article/491ec36ed417444fbad31b59c7c94166