Deep-learning empowered super-resolution plankton imaging
ACRONYM
SuperPI
Title
Deep-learning empowered super-resolution plankton imaging
General information
The goal of SuperPI is to develop AI-based methods for pushing the boundaries of
optical microscopy and plankton imaging technology. Plankton imaging systems, like all
microscopic systems, are limited by the trade-off between magnification and depth-of-field
(DOF) that restricts analysis to very small sample volumes. Recent technical advances in
opto-electronics, such as electrically tunable lenses (ETL), show great promise to overcome
this challenge by substantially enhancing the DOF. However, acquired images still suffer
from sub-optimal optical resolution due to the interference of in-focus and out-of-focus
objects during image formation. SuperPI will explore the potential of AI-based solutions for
maximizing the optical resolution of enhanced-DOF images acquired with modern ETL
technology. We will develop a physics-informed neural network (Pi-NN) to achieve
鈥渟uper-resolution imaging鈥� in unprecedentedly large sample volumes. Furthermore, the
results from this deep-learning based optical model will be used to facilitate object
recognition in the high-resolution EDOF images. Altogether, SuperPI will represent a
significant step forward in enhanced-DOF imaging that will not only advance plankton
imaging technology, but also benefit a wide range of other applications in optical microscopy.
Start
January, 2022
End
December, 2024
Funding (total)
200000
Funding (91探花)
133000
Funding body / Programme
-
Helmholtz-Gemeinschaft
/ Helmholtz AI - Artificial Intelligence Cooperation Unit (Impuls- und Vernetzungsfonds)
Coordination
Helmholtz-Zentrum f眉r Ozeanforschung Kiel (91探花), Germany
Contact
Partners
Helmholtz-Zentrum M眉nchen ( HMGU), Germany
