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Showing results 4 to 23 of 34 < previous   next >
Issue DateTitleInvolved Person(s)
30-Aug-2017Big Data : machine learning to identify shape biomarkers in intracranial aneurysmHirsch, Sven; Juchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel
18-Aug-2023Circle of Willis configurations in stroke patientsMusio, Fabio; Juchler, Norman; Yang, Kaiyuan; Menze, Björn; Hirsch, Sven
4-Oct-2018Clinical data sharing : a data scientist's perspectiveJuchler, Norman; Schilling, Sabine; Watanabe, Kazuhiro; Anzai, Hitomi; Rüfenacht, Daniel, et al
8-Feb-2018Correlation of CFD with wall enhancementAnzai, Hitomi; Juchler, Norman; Bilenga, Philippe; Rüfenacht, Daniel; Wanke, Isabel, et al
6-Jul-2023Determine atrial fibrillation burden with a photoplethysmographic mobile sensor: the atrial fibrillation burden trial : detection and quantification of episodes of atrial fibrillation using a cloud analytics service connected to a wearable with photoplethysmographic sensorReissenberger, Pamela; Serfözö, Peter; Piper, Diana; Juchler, Norman; Glanzmann, Sara, et al
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
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
2019Identification of clinically relevant characteristics of intracranial aneurysm morphologyJuchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Rüfenacht, Daniel; Kurtcuoglu, Vartan, 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
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
26-Jun-2023Radiological feature heterogeneity supports etiological diversity among patient groups in Meniere's diseaseBächinger, David; Filidoro, Noemi; Naville, Marc; Juchler, Norman; Kurtcuoglu, Vartan, et al
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
4-Jun-2020Shape irregularity of the intracranial aneurysm lumen exhibits diagnostic valueJuchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Morel, Sandrine; Rüfenacht, Daniel, et al
3-May-2022Shape trumps size : image-based morphological analysis reveals that the 3D shape discriminates intracranial aneurysm disease status better than aneurysm sizeJuchler, Norman; Schilling, Sabine; Bijlenga, Philippe; Kurtcuoglu, Vartan; Hirsch, Sven