Showing results 11 to 30 of 42
< previous
next >
Issue Date | Title | Involved Person(s) |
2018 | Effect of input image representation for results of neural network to detect cerebral aneurysms | Watanabe, Kazuhiro; Anzai, Hitomi; Juchler, Norman; Hirsch, Sven; Bijlenga, Philippe, et al |
2021 | Effects of low and high aneurysmal wall shear stress on endothelial cell behavior : differences and similarities | Morel, Sandrine; Schilling, Sabine; Diagbouga, Mannekomba R.; Delucchi, Matteo; Bochaton-Piallat, Marie-Luce, et al |
2017 | Endothelial cell elongation under shear stress : a computational model to consolidate observed cell shape changes | Schilling, Sabine; Morel, Sandrine; Bochaton-Piallat, Marie-Luce; Kwak, Brenda; Hirsch, Sven |
2022 | Exploring intracranial aneurysm instability markers to improve disease modeling | Dupuy, Nicolas; Juchler, Norman; Morel, Sandrine; Kwak, Brenda R.; Hirsch, Sven, et al |
Jul-2019 | Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics | Detmer, Felicitas J.; Hadad, Sara; Chung, Bong Jae; Mut, Fernando; Slawski, Martin, et al |
30-Oct-2018 | External validation of cerebral aneurysm rupture probability model with data from two patient cohorts | Detmer, Felicitas J.; Fajardo-Jiménez, Daniel; Mut, Fernando; Juchler, Norman; Hirsch, Sven, et al |
16-Nov-2020 | Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors | Bakker, Mark K.; van der Spek, Rick A. A.; van Rheenen, Wouter; Morel, Sandrine; Bourcier, Romain, et al |
2019 | Identification of clinically relevant characteristics of intracranial aneurysm morphology | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel; Kurtcuoglu, Vartan, et al |
1-Feb-2020 | Incorporating variability of patient inflow conditions into statistical models for aneurysm rupture assessment | Detmer, Felicitas J.; Mut, Fernando; Slawski, Martin; Hirsch, Sven; Bijlenga, Philippe, et al |
21-Jan-2020 | Influence of input image configurations on output of a convolutional neural network to detect cerebral aneurysms | Watanabe, Kazuhiro; Anzai, Hitomi; Juchler, Norman; Hirsch, Sven; Ohta, Makoto |
2022 | Intracranial aneurysm classifier using phenotypic factors : an international pooled analysis | Morel, Sandrine; Hostettler, Isabel C.; Spinner, Georg R.; Bourcier, Romain; Pera, Joanna, et al |
2015 | Intracranial aneurysms rupture risk clinical assessment | Bijlenga, Philippe; Hirsch, Sven |
7-Sep-2017 | Measuring the perceived morphological complexity of intracranial aneurysms | Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Kurtcuoglu, Vartan; Hirsch, Sven |
2022 | Modeling the location-dependency of aneurysm shape : a morphometric comparative study | Juchler, Norman; Bijlenga, Philippe; Hirsch, Sven |
15-Sep-2015 | On the utility of 3D Zernike Moment Invariants to assess aneurysm disease status | Juchler, Norman; Ebnöther, Ueli; Schilling, Sabine; Hirsch, Sven; Kurtcuoglu, Vartan |
2017 | PHASES score for the management of intracranial aneurysm | Bijlenga, Philippe; Gondar, Renato; Schilling, Sabine; Morel, Sandrine; Hirsch, Sven, et al |
1-Jul-2019 | Plea for an international Aneurysm Data Bank : description and perspectives | Bijlenga, Philippe; Morel, Sandrine; Hirsch, Sven; Schaller, Karl; Rüfenacht, Daniel |
17-Mar-2020 | Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms | Juchler, Norman; Schilling, Sabine; Glüge, Stefan; Bijlenga, Philippe; Rüfenacht, Daniel, et al |
2019 | Real and assumed insights : statistical models and imaging biomarkers for disease characterization of intracranial aneurysms | Hirsch, Sven; Juchler, Norman |
12-Jul-2018 | Reproducing qualitative irregularity ratings by means of quantitative shape descriptors in intracranial aneurysms | Juchler, Norman; Schilling, Sabine; Philippe, Bijlenga; Rüfenacht, Daniel; Kurtcuoglu, Vartan, et al |