Machine learning for large-scale volumetric microscopy in biology (Conference Presentation)

Ivo Sbalzarini

doi:10.1117/12.2631600

4 October 2022 Machine learning for large-scale volumetric microscopy in biology (Conference Presentation)

Ivo Sbalzarini

Proceedings Volume PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022; PC122040B (2022) https://doi.org/10.1117/12.2631600
Event: SPIE Nanoscience + Engineering, 2022, San Diego, California, United States

Abstract

Understanding how cells form tissues and how organs grow into their final shape relies on direct observation of these self-organization processes in living specimen. In cell and developmental biology, such observations are made possible by recent breakthroughs in volumetric 3D live microscopy, providing tissue-level data at sub-cellular resolution. These 3D+time datasets allow us to directly observe the processes of life, but they also define a new set of computer-science challenges: How to store and process Terabyte-sized 3D images? How to learn physical principles from them? How to visualize data at rates of several Gigabytes per second? This has given rise to the field of big-data bio-image informatics. In my talk, I will give an overview of the approaches we developed over the past few years. I will present a novel image representation, the Adaptive Particle Representation, which can replace the traditional pixel grids in such applications. I will show how the APR has enabled real-time processing and visualization of very large microscopy volumes, and how one can adapt convolutional neural networks to natively operate on this representation without intermediately having to go back to pixels. Finally, I highlight some recent advancements in statistical learning theory that enable us to learn interpretable and physically consistent active matter models directly from noisy microscopy videos, closing the loop back to the initial physical hypothesis of tissue self-organization.

Conference Presentation

Citation Download Citation

Ivo Sbalzarini "Machine learning for large-scale volumetric microscopy in biology (Conference Presentation)", Proc. SPIE PC12204, Emerging Topics in Artificial Intelligence (ETAI) 2022, PC122040B (4 October 2022); https://doi.org/10.1117/12.2631600

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KEYWORDS

Microscopy

Biology

Machine learning

Tissues

3D image processing

Image processing

Video microscopy

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