Strengths and challenges of diversity: Correlative analysis of multimodal image data
November 15, 2024 @ 10:00 – 11:00 CET
Nataša Sladoje, Uppsala University
NBIS arranges an open AI and IO Seminar Series aimed at knowledge-sharing about Artificial Intelligence and Integrative Omics (AI & IO) analysis and applications in the Life Science community. The seminar series is open to everyone. The seminar is run over Zoom on the third Friday of the month during academic terms, typically between 10 and 11 am, with approx. 45 min presentation and 15 min discussion.
Abstract
The MIDA (Methods for Image Data Analysis) group, at Dept of Information Technology, Uppsala University, focuses on development of methods which address challenges of biomedical visual data analysis, while also being broadly applicable to other types of images. I will give a short overview of our different research projects and collaborative initiatives, and will then focus on our experiences and results in multimodal (bio)image analysis.
Multimodal imaging gives an opportunity to collect diverse and complementary information about a specimen, enabling a deeper understanding of complex systems and phenomena. This advantage comes at the cost of a typically very demanding and challenging data analysis. Successful correlative analysis of the collected data requires accurate automated alignment of multimodal images and efficient information fusion to maximize the gain from the available heterogeneous and complementary content. I will present our results in this context and will discuss our experiences gained in method development and their application.
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