Roadmap on deep learning for microscopy
Review article, 2026
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning (ML) are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap encompasses key aspects of how ML is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of ML for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.
AI
deep learning
imaging
microscopy
Author
Giovanni Volpe
University of Gothenburg
Carolina Wahlby
Uppsala University
Lei Tian
Boston University
Michael Hecht
CASUS
University of Wrocław
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Artur Yakimovich
University College London (UCL)
University of Wrocław
Roche Diagnostics
CASUS
Artificial Intelligence for Life Sciences (CIC)
Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
Kristina Monakhova
University of California
Laura Waller
University of California
Ivo F. Sbalzarini
Technische Universität Dresden
Christopher A. Metzler
University of Maryland
Mingyang Xie
University of Maryland
Kevin Zhang
University of Maryland
Isaac C. D. Lenton
IST Austria (ISTA)
University of Queensland
Halina Rubinsztein-Dunlop
University of Queensland
ARC Centre of Excellence in Quantum Biotechnology
Daniel Brunner
University of Franche-Comté
Bijie Bai
University of California
Aydogan Ozcan
University of California
Daniel Midtvedt
University of Gothenburg
Hao Wang
Boston University
Tongyu Li
Boston University
Natasa Sladoje
Uppsala University
Joakim Lindblad
Uppsala University
Jason T. Smith
ECS Federal
Rensselaer Polytechnic Institute
Marien Ochoa
University of Wisconsin Madison
Uppsala University
Margarida Barroso
Albany Medical College
Xavier Intes
Rensselaer Polytechnic Institute
Tong Qiu
Massachusetts Institute of Technology (MIT)
Li-Yu Yu
Massachusetts Institute of Technology (MIT)
Sixian You
Massachusetts Institute of Technology (MIT)
Yongtao Liu
Oak Ridge National Laboratory
Maxim A. Ziatdinov
Oak Ridge National Laboratory
Kalinin
University of Tennessee
Arlo Sheridan
Salk Institute for Biological Studies
Uri Manor
Salk Institute for Biological Studies
University of California
Elias Nehme
Technion – Israel Institute of Technology
Ofri Goldenberg
Technion – Israel Institute of Technology
Yoav Shechtman
Technion – Israel Institute of Technology
Henrik Klein Moberg
Chalmers, Physics, Chemical Physics
Christoph Langhammer
Chalmers, Physics, Chemical Physics
Barbora Spackova
Czech Academy of Sciences
Saga Helgadottir
Stockholm University
Uppsala University
Benjamin Midtvedt
University of Gothenburg
Aykut Argun
University of Gothenburg
Tobias Thalheim
Leipzig University
Frank Cichos
Leipzig University
Stefano Bo
Max Planck Society
King's College London
Lars Hubatsch
Max Planck Society
Jesus Pineda
University of Gothenburg
Carlo Manzo
Forest Sciences Centre of Catalonia
Harshith Bachimanchi
University of Gothenburg
Erik Selander
Lund University
Antoni Homs-Corbera
OWL Lifesciences
SAS
Martin Franzl
Leipzig University
Kevin De Haan
University of California
Yair Rivenson
University of California
Zofia Korczak
University of Gothenburg
Caroline Beck Adiels
University of Gothenburg
Mite Mijalkov
Karolinska Institutet
Daniel Vereb
Karolinska Institutet
Yu-Wei Chang
University of Gothenburg
Joana B. Pereira
Karolinska Institutet
Damian Matuszewski
Uppsala University
Gustaf Kylberg
VINNOVA
Ida-Maria Sintorn
VINNOVA
Uppsala University
Juan C. Caicedo
University of Wisconsin Madison
Beth A. Cimini
Massachusetts Institute of Technology (MIT)
Muyinatu A. Lediju Bell
Johns Hopkins University
Bruno M. Saraiva
Instituto Gulbenkian de Ciência (IGC)
Guillaume Jacquemet
Åbo Akademi
University of Turku
Ricardo Henriques
University College London (UCL)
Instituto Gulbenkian de Ciência (IGC)
Wei Ouyang
Royal Institute of Technology (KTH)
Trang Le
Stanford University
Estibaliz Gomez-de-Mariscal
Instituto Gulbenkian de Ciência (IGC)
Nova University of Lisbon
Daniel Sage
Swiss Federal Institute of Technology in Lausanne (EPFL)
Arrate Munoz-Barrutia
Gregorio Maranon Health Research Institute
Universidad Carlos III de Madrid
Ebba Josefson Lindqvist
AI Sweden
Johanna Bergman
AI Sweden
JPhys Photonics
25157647 (eISSN)
Vol. 8 1 012501Subject Categories (SSIF 2025)
Medical Imaging
DOI
10.1088/2515-7647/ae0fd1