6 - Beyond the Patterns - Mauricio Reyes - Medical image analysis in the era of deep learning: From performance to challenging the alchemist within/ClipID:25054 previous clip next clip

Recording date 2020-11-26

Via

Free

Language

English

Organisational Unit

Friedrich-Alexander-Universität Erlangen-Nürnberg

Producer

Friedrich-Alexander-Universität Erlangen-Nürnberg

It is a great pleasure to present this invited talk by Mauricio Reyes from the University of Bern on his great research in the field of Machine Learning and Medical Imaging:

Title: Medical image analysis in the era of deep learning: From performance to challenging the alchemist within
Prof. Dr. Mauricio Reyes, University Bern

Abstract: In this talk, Dr. Reyes will present our experience in the area of deep learning-based medical image analysis, going through the classical pillars of obtaining high accuracy, through then focusing on issues preventing clinical integration, including robustness, system monitoring via human-machine interfaces, interpretability and fast active learning. The talk will focus on neuroimaging but a few examples in other areas will be provided.

Biosketch: Mauricio Reyes, conducted graduate studies in Electrical Engineering at the University of Santiago, Chile where he was awarded the best electrical engineer thesis by the Chilean Institute of Engineers School. He conducted postgraduate studies to obtain a Ph.D. in Computer Sciences with a specialization in Medical Image Analysis from INRIA, France (2006). He is an associate professor at the medical faculty of the University of Bern and is currently leading the Medical Image Analysis group at the ARTORG Center for Biomedical Engineering Research of the University of Bern. His research focuses on basic and applied machine learning technologies as well as biomedical engineering solutions to improve healthcare through medical image computation technologies. A particular strength of his research has been the emphasis on developing solutions that are designed to be integrated into the clinical workflow. Dr. Reyes has participated in several Swiss National Science Foundation projects, Commission of Technology and Innovation projects, EU-FP7 projects on computational oncology and computational anatomy, and several further projects supported by Swiss foundations. From 2006 he has secured over 7.6M EUR research funds. He has an H-index: 34, has authored over 230 articles, with over 6000 citations. His entrepreneurial work has also led to the creation of one consolidated company and the second one in its first steps.

References

Suter Y., Knecht U., Alao M., Valenzuela W., Hewer E., Schucht P., Wiest R., and Reyes M. Radiomics for glioblastoma survival analysis in pre-operative mri: Exploring feature robustness, class boundaries, and machine learning techniques. Cancer Imaging, 20(2):1-13, June 2020.

Jungo A., Balsiger F., and Reyes M. Analyzing the quality and challenges of uncertainty estimations for brain tumor segmentation. Frontiers in Neuroscience, 14:282, 2020. Jungo A. and Reyes M. Assessing reliability and challenges of uncertainty estimations for medical image segmentation. In Medical Image Computing and Computer-Assisted Intervention { MICCAI 2019 , volume In Press of Lecture Notes in Computer Science, 2019.

Silva W., Cardoso J., and Reyes M. Interpretability-guided content-based medical image retrieval. In Medical Image Computing and Computer-Assisted Intervention { MICCAI 2020, volume In Press, 2020.

Reyes M., Meier R., Pereira S., Silva C., Dahlweid FM., von Teng-Kobligk H., Summers R., and Wiest R. On the interpretability of artificial intelligence in radiology: Challenges and opportunities. Radiology: Articial Intelligence , 2(3):e190043, 2020.

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Music Reference: Damiano Baldoni - Thinking of You

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