[Statlist] Reminder: ETH/UZH ZüKoSt: Seminar on Applied Statistics by Bjoern Menze, University of Zurich, Department of Quantitative Biomedicine, 10.12.2021

[Maurer Letizia]

We are glad to announce the following talk in the ETH/UZH ZüKoSt: Seminar on Applied Statistics:

"Biomedical Image Analysis and Machine Learning"   
by Bjoern Menze, University of Zurich, Department of Quantitative Biomedicine

Time: Friday,  10.12.2021 at 15.15 h
Place: https://uzh.zoom.us/j/69988963817?pwd=Yis5STc1OWJxY0tGU1VKMXVYNXVJdz09
Meeting ID: 699 8896 3817
Passcode: 267935

Abstract: Biomedical image data offers quantitative information about health, disease, and disease progression under treatment - both at the patient and at the population level. Computational routines are instrumental in extracting these information in a structured fashion, typically following a succession of image segmenation, 'radiomic' feature extraction, and predictive modeling with respect to a given image marker or disease-related outcome. This pipeline can also be complemented by a functional and patient-specific modeling of the features or processses underlying the given image observations, for example, the tumor-growth underlying a set of magnetic resonance scans acquired prior to and after treatment.

I will talk about this image processing pipeline, together open problems that we continue to work in Zurich, focusing on two aspects: a) the development and benchmarking of image segmenation routines in the 'Multi-modal Brain Tumor Image Segmentation Benchmark' (BRATS), one of the largest benchmark challenges in biomedical image computing, and b) the image-based modeling of tumor growth using partial differential equations, and a fast personalization and inversion of those models via neural networks.

Seminar website: https://math.ethz.ch/sfs/news-and-events/seminar-applied-statistics.html


Organisers: F. Balabdaoui, A. Bandeira, P. L. Bühlmann, R. Furrer, L. Held, T. Hothorn, M. Kalisch, M. H. Maathuis, M. Mächler, L. Meier, M. Robinson, C. Strobl, S. van de Geer