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Thursday,
30 Jan 2025 |
Video-Recording for any system with MP4-support - Video.mp4 (ca. 473 Mb) |
15:15 – 16:30 |
"How can deep learning enhance microscopy?"
Prof. Giovanni Volpe
(University of Gothenburg)
Abstract:
Video microscopy has a long history of
providing insights and breakthroughs for a
broad range of disciplines, from physics
to biology. Image analysis to extract
quantitative information from video
microscopy data has traditionally relied on
algorithmic approaches, which are often
difficult to implement, time consuming,
and computationally expensive. Recently,
alternative data-driven approaches using
deep learning have greatly improved
quantitative digital microscopy, potentially
offering automatized, accurate, and fast
image analysis. However, the combination
of deep learning and video microscopy
remains underutilized primarily due to the
steep learning curve involved in
developing custom deep-learning solutions.
To overcome this issue, we have introduced
a software, currently at version
DeepTrack 2.2, to design, train and
validate deep-learning solutions for
digital microscopy.
A list of references is available on the
event webpage:
https://indico.fysik.su.se/event/8867/
About the speaker:
Giovanni Volpe is Full Professor at the
Physics Department of the University of
Gothenburg, where he leads the Soft Matter
Lab (http://softmatterlab.org).
His research interests include soft
matter, optical trapping and manipulation,
statistical mechanics, brain connectivity,
and machine learning. He has authored
more than 100 articles and reviews on soft
matter, statistical physics, optics,
physics of complex systems, brain network
analysis, and machine learning.
He co-authored the books "Optical
Tweezers: Principles and Applications"
(Cambridge University Press, 2015) and
“Simulation of Complex Systems”
(IOP Press, 2021). He has developed
several software packages for optical
tweezers (OTS — Optical Tweezers Software),
brain connectivity (BRAPH—
Brain Analysis Using Graph Theory), and
microscopy enhanced by deep learning
(DeepTrack). He's now co-author of the
book "Deep Learning Crash Course"
(No Starch Press, 2025).