Introduction
Immunotherapy has become a life-saving option for advanced cancer patients.
However, only a minority of patients develop a durable response. Despite great
efforts to explain the variable responses to immunotherapy and to optimize
patient selection, current diagnostic tools cannot sufficiently guide clinical
practice. This project combines state-of-the-art multiplexed immunofluorescence
microscopy with the latest techniques in image processing and deep learning to
advance the understanding of how cell interrelations in the tumor microenvironment
affect the disease progression and treatment efficacy.
Starting from a large collection of acquired multispectral histology images, we aim to develop advanced interpretable AI-driven approaches for characterization of the structural organization and interrelations of different cell types, enabling reliable and explainable prediction of patient disease progression. Directions we are exploring include multi-channel image-based analysis, geometric data representations such as cell graphs and point clouds, multi-modal approaches with H&E histology, and extending the analysis to three dimensions through tissue volume reconstruction.
The project heavily relies on interdisciplinary competences and is conducted in close collaboration with Patrick Micke's group at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University.
Starting from a large collection of acquired multispectral histology images, we aim to develop advanced interpretable AI-driven approaches for characterization of the structural organization and interrelations of different cell types, enabling reliable and explainable prediction of patient disease progression. Directions we are exploring include multi-channel image-based analysis, geometric data representations such as cell graphs and point clouds, multi-modal approaches with H&E histology, and extending the analysis to three dimensions through tissue volume reconstruction.
The project heavily relies on interdisciplinary competences and is conducted in close collaboration with Patrick Micke's group at the Department of Immunology, Genetics and Pathology (IGP) at Uppsala University.
More headers?
More info about methods/subprojects, publications, data, involved people, etc.
Funding
This research is funded by:
- Swedish Research Council Project number 2022-03580,
- Cancerfonden (Swedish Cancer Society) Project number 22 2357 Pj,
- AIDA (VINNOVA's MedTech4Health project 2017-02447),
- eSSENCE graduate school.