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