Statusvortrag im Promotionsver­fahren von Frau Sheida Rahnamai Kordasiabi

Abstract:

In recent years, advances in imaging technologies have transformed the life sciences, enabling the observation of biological structures and dynamics at unprecedented resolution. This explosion in data offers immense opportunities for discovery but also poses significant computational challenges. My PhD research addresses two fundamental problems in biological image analysis: the segmentation of cellular structures in electron microscopy (EM) images and the tracking of cells in fluorescence microscopy time-lapse sequences.

Although segmentation and tracking are well-studied tasks, biological imaging data presents unique obstacles such as high noise, low contrast, crowded morphologies, and domain-specific constraints that limit the effectiveness of general-purpose tools. My work focuses on developing computational methods that are accurate, scalable, and biologically informed, bridging theory and application. In particular, I have designed a principled segmentation framework tailored to the complexities of EM data and explored innovative approaches to tracking that emphasize robustness and interpretability.

This talk will outline the trajectory of my research, highlight key methodological contributions, and reflect on how biological imaging continues to inspire the development of new computational techniques.