Running Projects

Runtime of the project: 01.03.2023 -28.02.2028

Project Funding Body:  LOOP Zurich Program

Main-PI: Prof. Felix Beuschlein (USZ)

Co-PIs: Prof. Thomas Frauenfelder (USZ), Prof. Ender Konukoglu, Prof. Milo Pulan (UZH), Prof. Christian Wolfrum

Runtime of the project: 01.01.2023 -31.12.2024

Project Funding Body:  PHRT/ETH

Main-PI: Prof. Sebastian Kozerke (ETH)

Co-PIs: Prof. Ender Konukoglu, Dr. Markus Holzner (WSL), Prof. Michael Unser (EPFL), Prof. Tristan van Doormaal (USZ), PD DR. Zsolt Kulscsar (USZ)

Runtime of the project: 01.12.2022 -30.11.2025

Project Funding Body:  PHRT/ETH

Main-PI: Prof. Grégoire Courtine (EPFL)

Co-PIs: Prof. Ender Konukoglu, Dr. Guillaume Obozinski (SDSC), Prof. Jocelyne Bloch (Lausanne University Hospital), Dr. Esra Neufeld (IT'IS foundation), Dr. John Murphy (onward Medical)

Runtime of the project: 01.02.2023 -31.01.2025

Project Funding Body:  PHRT/ETH

Co-PI: Prof. Jean-Phlippe Thiran (EPFL)

Runtime of the project: 01.05.2021 -30.04.2025

Project Funding Body: SNF

 

01.01.2019 - 31.12.2024

Main Applicants:
Prof. Jürg Hodler (University Hospital Zurich)
Prof. Matthias Guckenberger (University Hospital Zurich)

Co-Applicants:
Prof. Nicolaus Andratschke (University Hospital Zurich)
Prof. Andreas Boss, Radiology (University Hospital Zurich)
Prof. Ralph Braun, Dermatology (University Hospital Zurich)
Prof. Andrew Hall (University Zurich)
Prof. Philipp Kaufmann (University Hospital Zurich)
Prof. Ender Konukoglu (ETH Zurich)
PD Dr. Cristina Rossi (University Zurich)
Prof. Christoph Stippich (University Hospital Zurich)
Prof. Jan Unkelbach (University Zurich)

Artificial Intelligence (AI) methods are rapidly developing in all fields of human life sciences and are already applied in medical application for certain image processing tasks. They are expected to further revolutionize the work of physicians and all other medical professions. AI techniques promise improvements in two directions:

1) they allow fast and robust automation and standardization of routine tasks on large scale image data such as image segmentation or volume measurements which are currently labor-intensive manual tasks;

2) algorithms for quantitative image analysis facilitate the detection of imaging features and patterns (radiomics) not perceivable to the human eye, which correlate with clinical outcome or underlying disease biology. Considering the everincreasing amount of imaging data acquired for cancer patients, computer algorithms are expected to outperform humans in analyzing the complex information of these images. Large international companies such as Google, IBM or Microsoft are investing heavily to get power in this area with
potentially far-reaching consequences for patients, physicians, healthcare organizations, and the scientific community. Additionally, AI technology will need to be integrated into clinical expert systems for multidisciplinary and multi-professional cancer diagnosis and care to fully explore its potential.

In the Clinical Research Priority Program, the competences of physicians and scientists from the University Hospital Zürich, the University Zürich, and the ETH Zürich will be combined to explore the potential of AI in oncological imaging. The network will exploit interdisciplinary synergies between clinical disciplines, translational research, and theoretical laboratories in the application of AI techniques. As knowledge of these methodologies is recognized as a core competence for the next generation of scientist and medical doctors, a strong emphasis has been put on developing an educational curriculum for the young scientists who will be supported and mentored by this proposal.

Specific aims of the network are
(i) To build a powerful network of AI research in oncological imaging at USZ, UZH, and ETHZ,
(ii) To promote state-of-the-art AI research for interdisciplinary oncological research projects,
(iii) To accelerate translation from theoretical to clinical science,
(iv) To build a common AI platform compatible with the clinical environment,
(v) To foster young scientists in the development of AI competencies.

Runtime of the project: 01.09.2021 -31.03.2024

Project Funding Body: PHRT/ETH

Research Partner ETH: Prof. Sebastian Kozerke

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