Dr. Norman Juchler

Netzwerk

Mitglied in Netzwerken

• AneuX
• The Interface Group
• Digital Futures Lab
• Center for Computational Health
• Digital Health Lab
• Datalab

ORCID digital identifier

ORCID ID: 0000-0001-8518-7211

Projekte

• GEMINI: Mehrskalige digitale Zwillinge (Digital Twins) für Patient:innen mit ischämischem oder hämorrhagischem Schlaganfall / Stellv. Projektleiter:in / laufend
• Stroke DynamiX – Graphische und kausale Netzwerke für das personalisierte Schlaganfallmanagement / Teammitglied / abgeschlossen
• OSR4H – Open Set Recognition for Hematology / Teammitglied / abgeschlossen
• Deep Brain Vessel Profiler / Teammitglied / abgeschlossen
• Smart Hospital – Integrated Framework, Tools & Solutions / Teammitglied / abgeschlossen
• Die Exploration der Gen-Harmonisierung / Teammitglied / abgeschlossen
• AneuX Modeling – Shape as a Biomarker for Instability of Intracranial Aneurysms / Teammitglied / abgeschlossen
• Intracranial Aneurysm Database / Teammitglied / abgeschlossen

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed

• Musio, F., Juchler, N., Yang, K., Shit, S., Prabhakar, C., Menze, B., & Hirsch, S. (2026). Circle of Willis centerline graphs : a dataset and baseline algorithm. Neuroscience Informatics, 6(1), 100265. https://doi.org/10.1016/j.neuri.2026.100265
• Reissenberger, P., Serfözö, P., Piper, D., Juchler, N., Glanzmann, S., Gram, J., Hensler, K., Tonidandel, H., Börlin, E., D’Souza, M., Badertscher, P., & Eckstein, J. (2023). Determine 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 sensor. European Heart Journal - Digital Health, 4(5), 402–410. https://doi.org/10.1093/ehjdh/ztad039
• Bächinger, D., Filidoro, N., Naville, M., Juchler, N., Kurtcuoglu, V., Nadol, J. B., Schuknecht, B., Kleinjung, T., Veraguth, D., & Eckhard, A. H. (2023). Radiological feature heterogeneity supports etiological diversity among patient groups in Meniere’s disease. Scientific Reports, 13(1), 10303. https://doi.org/10.1038/s41598-023-36479-5
• Mack, I., Juchler, N., Rey, S., Hirsch, S., Hoelz, B., Eckstein, J., & Bielicki, J. (2022). Wearable technologies for pediatric patients with surgical infections : more than counting steps? Biosensors, 12(8), 634. https://doi.org/10.3390/bios12080634
• Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2022). Shape trumps size : image-based morphological analysis reveals that the 3D shape discriminates intracranial aneurysm disease status better than aneurysm size. Frontiers in Neurology, 13(809391). https://doi.org/10.3389/fneur.2022.809391
• Juchler, N., Schilling, S., Bijlenga, P., Morel, S., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2020). Shape irregularity of the intracranial aneurysm lumen exhibits diagnostic value. Acta Neurochirurgica, 162(9), 2261–2270. https://doi.org/10.1007/s00701-020-04428-0
• Juchler, N., Schilling, S., Glüge, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2020). Radiomics approach to quantify shape irregularity from crowd-based qualitative assessment of intracranial aneurysms. Computer Methods in Biomechanics and Biomedical Engineering : Imaging & Visualization, 8(5), 538–546. https://doi.org/10.1080/21681163.2020.1728579
• Detmer, F. J., Hadad, S., Chung, B. J., Mut, F., Slawski, M., Juchler, N., Kurtcuoglu, V., Hirsch, S., Bijlenga, P., Uchiyama, Y., Fujimura, S., Yamamoto, M., Murayama, Y., Takao, H., Koivisto, T., Frösen, J., & Cebral, J. R. (2019). Extending statistical learning for aneurysm rupture assessment to Finnish and Japanese populations using morphology, hemodynamics, and patient characteristics. Neurosurgical Focus, 47(1). https://doi.org/10.3171/2019.4.FOCUS19145
• Detmer, F. J., Fajardo-Jiménez, D., Mut, F., Juchler, N., Hirsch, S., Pereira, V. M., Bijlenga, P., & Cebral, J. R. (2018). External validation of cerebral aneurysm rupture probability model with data from two patient cohorts. Acta Neurochirurgica. https://doi.org/10.1007/s00701-018-3712-8

Bücher, peer-reviewed

Juchler, N. (2020). Shape-based analysis of intracranial aneurysms [Doctoral dissertation, University of Zurich]. https://doi.org/10.5167/uzh-200995

Schriftliche Konferenzbeiträge, peer-reviewed

• Juchler, N., Bijlenga, P., & Hirsch, S. (2022). Modeling the location-dependency of aneurysm shape : a morphometric comparative study [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 2, pp. 703–705). Computational & Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25388
• Juchler, N., Bijlenga, P., & Hirsch, S. (2022). The role of shape for aneurysm risk assessment [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 84–86). Computational & Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25386
• Dupuy, N., Juchler, N., Morel, S., Kwak, B. R., Hirsch, S., & Bijlenga, P. (2022). Exploring intracranial aneurysm instability markers to improve disease modeling [Conference paper]. In P. Nithiarasu & C. Vergara (Eds.), CMBE 2022 : 7th International Conference on Computational & Mathematical Biomedical Engineering (Vol. 1, pp. 14–17). Computational and Mathematical Biomedical Engineering. https://doi.org/10.21256/zhaw-25387
• Watanabe, K., Anzai, H., Juchler, N., Hirsch, S., & Ohta, M. (2020). Influence of input image configurations on output of a convolutional neural network to detect cerebral aneurysms [Conference paper]. International Mechanical Engineering Congress and Exposition : Volume 3 - Biomedical and Biotechnology Engineering, 3. https://doi.org/10.1115/IMECE2019-11125
• Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2019). Understanding morphological irregularity : a rater-based study [Conference paper]. CMBE19 Proceedings, 583.
• Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2019). Identification of clinically relevant characteristics of intracranial aneurysm morphology. 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019.
• Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2017). Measuring the perceived morphological complexity of intracranial aneurysms [Conference poster]. Abstract Book, 3rd International SystemsX.ch Conference on Systems Biology, 160. https://doi.org/10.3929/ethz-b-000176201
• Juchler, N., Schilling, S., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2016, September 1). Shape-based assessment of intracranial aneurysm disease status – a machine learning approach. All SystemsX.ch Day, Bern, 1 September 2016.
• Juchler, N., Schilling, S., Vartan, K., & Hirsch, S. (2016, June 29). What’s ugly? : shape-based analysis of intracranial aneurysms. Latsis Symposium 2016 : Personalized Medicine, Zurich, 27-29 June 2016.
• Juchler, N., Ebnöther, U., Schilling, S., Hirsch, S., & Kurtcuoglu, V. (2015, September 15). On the utility of 3D Zernike Moment Invariants to assess aneurysm disease status. All SystemsX.ch Day, Bern, 15 September 2015.

Weitere Publikationen

Juchler, N., Schilling, S., Vartan, K., & Hirsch, S. (2016, September 15). Shape-based assessment of intracranial aneurysm disease status. ZNZ Symposium 2016, Zurich, 15. September 2016.

Mündliche Konferenzbeiträge und Abstracts

• Musio, F., Juchler, N., Yang, K., Menze, B., & Hirsch, S. (2023, August 18). Circle of Willis configurations in stroke patients. 19th Interdisciplinary Cerebrovascular Symposium, Geneva, Switzerland, 17-19 August 2023.
• Hirsch, S., & Juchler, N. (2019). Real and assumed insights : statistical models and imaging biomarkers for disease characterization of intracranial aneurysms. 1. Digital Health Lab Day (Life in Numbers 5), Wädenswil, 3. October 2019.
• Watanabe, K., Anzai, H., Juchler, N., Hirsch, S., Bijlenga, P., & Ohta, M. (2018). Effect of input image representation for results of neural network to detect cerebral aneurysms. 31st Bioengineering Conference / 2018 Annual Meeting of BED/JSME, Koriyama, Japan, 14-15 December 2018.
• Juchler, N., Schilling, S., Watanabe, K., Anzai, H., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2018, October 4). Clinical data sharing : a data scientist’s perspective. Life in Numbers 4, Wädenswil, 4 October 2018.
• Juchler, N., Schilling, S., Philippe, B., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2018, July 12). Reproducing qualitative irregularity ratings by means of quantitative shape descriptors in intracranial aneurysms. 8th World Congress of Biomechanics (WCB2018), Dublin, Ireland, 8-12 July 2018.
• Juchler, N., Schilling, S., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2018, April 13). Aneurysm shape as a diagnostic tool. Kick-off Event: PhD Network in Data Science, Winterthur, 13. April 2018.
• Juchler, N., Schilling, S., Bijlenga, P., Rüfenacht, D., Kurtcuoglu, V., & Hirsch, S. (2018, February 8). Aneurysm shape as a diagnostic tool : a machine learning approach. International Neurovascular Exploratory Workshop (iNEW′2018), Zürich, 7-9 February 2018.
• Anzai, H., Juchler, N., Bilenga, P., Rüfenacht, D., Wanke, I., & Hirsch, S. (2018, February 8). Correlation of CFD with wall enhancement. iNEW, Zürich, 8. Februar 2018.
• Hirsch, S., Juchler, N., Schilling, S., Bijlenga, P., & Rüfenacht, D. (2018, January). Using machine learning to identify shape biomarkers in intracranial aneurysm. Life Science Zurich Impact, Zürich, 22 January 2018.
• Hirsch, S., Juchler, N., Schilling, S., Bijlenga, P., & Rüfenacht, D. (2017, August 30). Big Data : machine learning to identify shape biomarkers in intracranial aneurysm. Annual Meeting of the Swiss Society for Biomedical Engineering (SSBE), Winterthur, 30 August 2017.
• Anzai, H., Juchler, N., Ohta, M., Hirsch, S., Rüfenacht, D. A., & Wanke, I. (2017, April 12). Where does CFD identify lesion instability in small aneurysms? CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
• Juchler, N., Schilling, S., Wanke, I., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2017, April 12). Using shape descriptors to categorize intracranial aneurysms. CMBE17 : 5th International Conference on Computational and Mathematical Biomedical Engineering.
• Juchler, N., Schilling, S., Wanke, I., Rüfenacht, D., Bijlenga, P., Kurtcuoglu, V., & Hirsch, S. (2016, June 9). Shape-based modeling of aneurysmal disease status. ECCOMAS Congress 2016, Heraklion, Greece, 5-10 June 2016.

Forschungsdaten

Juchler, Norman; Bijlenga, Philippe; Hirsch, Sven, 2022. AneuX morphology database. Zenodo. Verfügbar unter: https://doi.org/10.5281/zenodo.6678442

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