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Presentation of research activities

Henning Müller leads the MedGIFT group on medical multimodal data analysis. The group’s research focuses on building decision support tools using medical data in the forms of images, signals, texts and structured data. Using machine learning predictions, classifications and segmentations can be made in the data. The tools are used on data from radiology, ophthalmology and increasingly histopathology using strong computer infrastructures and mainly deep learning. Interpretability and explainability of the machine learning outcomes are another strong focus of the group.

Henning Müller

Prof. Henning Müller studied medical informatics at the University of Heidelberg (Germany) then worked for Daimler-Benz in Portland (USA). He dedicated the years from 1998 to 2002 to his PhD at the University of Geneva (Switzerland), interspersed with a research tenure at Monash University (Australia) in 2001. Since 2002, Henning has been working in the field of medical informatics at the Geneva University Hospitals, where he received his diploma in 2008. He was appointed full professor in 2014.

Since 2007, Henning has worked as a computer science professor at the HES-SO Valais-Wallis in Sierre, and has since 2011 been in charge of the eHealth unit in Sierre as well. He was also the coordinator of the Khresmoi project, scientific coordinator of the VISCERAL project, and initiator of the ImageCLEF benchmark. He has written over 400 scientific articles, sits on the editorial board of several journals, and acts as reviewer for a number of journals and funding agencies throughout the world.

In 2015 & 2016, Pr. Müller was invited as a Visiting Professor to the Boston Martinos Center (USA), which is part of Harvard Medical School and the Massachusetts General Hospital (MGH), working on collaborative projects related to medical imaging and system evaluation, among others, within the Quantitative Imaging Network of the National Cancer Institutes.

HES-SO Valais-Wallis - Haute Ecole de Gestion
Route de la Plaine 2, Case postale 80
3960 Sierre
Switzerland

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Key publications

PubMed ORCID

A review of content-based image retrieval systems in medicine – clinical benefits and future directions

Henning Müller, Nicolas Michoux, David Bandon, Antoine Geissbuhler
International Journal of Medical Informatics volume 73, pages 1-23, 2004.

Performance Evaluation in Content-Based Image Retrieval: Overview and Proposals

Henning Müller, Wolfgang Müller, David McG. Squire, Stéphane Marchand-Maillet and Thierry Pun
Pattern Recognition Letters (Special Issue on Image and Video Indexing), 22, 5, pages 593-601, 2001. H. Bunke and X. Jiang Eds.

Unleashing the potential of digital pathology data by training computer-aided diagnosis models without human annotations

Niccolò Marini, Stefano Marchesin, Sebastian Otálora, Marek Wodzinski, Alessandro Caputo, Mart van Rijthoven, Witali Aswolinskiy, John-Melle Bokhorst, Damian Podareanu, Edyta Petters, Svetla Boytcheva, Genziana Buttafuoco, Simona Vatrano, Filippo Fraggetta, Jeroen van der Laak, Maristella Agosti, Francesco Ciompi, Gianmaria Silvello, Henning Muller, Manfredo Atzori
Nature Partner Journal on Digital Health, 2022.

A Global Taxonomy of Interpretable AI: Unifying the Terminology for the Technical and the Social Sciences

Mara Graziani, Lidia Dutkiewicz, Davide Calvaresi, José Pereira Amorim, Katerina Yordanova, Mor Vered, Rahul Nair, Pedro Henriques Abreu, Tobias Blanke, Valeria Pulignano, John O. Prior, Lode Lauwaert, Wessel Reijers, Adrien Depeursinge, Vincent Andrearczyk, Henning Müller
Artificial Intelligence Reviews, 2022.

Semi-supervised training of deep convolutional neural networks with heterogeneous data and few local annotations: an experiment on histopathology image classification

Niccolo Marini, Sebastian Otalora, Henning Müller, Manfredo Atzori
Medical image Analysis, 2021.