Roadmap on deep learning for microscopy
Reviewartikel, 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.
microscopy
deep learning
AI
imaging
Författare
Giovanni Volpe
Göteborgs universitet
Carolina Wahlby
Uppsala universitet
Lei Tian
Boston University
Michael Hecht
CASUS
Helmholtz-Gemeinschaft Deutscher Forschungszentren
Uniwersytet Wrocławski
Artur Yakimovich
Helmholtz-Gemeinschaft Deutscher Forschungszentren
CASUS
Roche Diagnostics
University College London (UCL)
Artificial Intelligence for Life Sciences (CIC)
Uniwersytet Wrocławski
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
University of Queensland
IST Austria (ISTA)
Halina Rubinsztein-Dunlop
University of Queensland
ARC Centre of Excellence in Quantum Biotechnology
Daniel Brunner
Université de Franche-Comté
Bijie Bai
University of California
Aydogan Ozcan
University of California
Daniel Midtvedt
Göteborgs universitet
Hao Wang
Boston University
Tongyu Li
Boston University
Natasa Sladoje
Uppsala universitet
Joakim Lindblad
Uppsala universitet
Jason T. Smith
ECS Federal
Rensselaer Polytechnic Institute
Marien Ochoa
University of Wisconsin Madison
Uppsala universitet
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
University of California
Salk Institute for Biological Studies
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, Fysik, Kemisk fysik
Christoph Langhammer
Chalmers, Fysik, Kemisk fysik
Barbora Spackova
Czech Academy of Sciences
Saga Helgadottir
Uppsala universitet
Stockholms universitet
Benjamin Midtvedt
Göteborgs universitet
Aykut Argun
Göteborgs universitet
Tobias Thalheim
Universität Leipzig
Frank Cichos
Universität Leipzig
Stefano Bo
Max-Planck-Gesellschaft
King's College London
Lars Hubatsch
Max-Planck-Gesellschaft
Jesus Pineda
Göteborgs universitet
Carlo Manzo
Centro Tecnológic Forestal de Catalunya
Harshith Bachimanchi
Göteborgs universitet
Erik Selander
Lunds universitet
Antoni Homs-Corbera
SAS
OWL Lifesciences
Martin Franzl
Universität Leipzig
Kevin De Haan
University of California
Yair Rivenson
University of California
Zofia Korczak
Göteborgs universitet
Caroline Beck Adiels
Göteborgs universitet
Mite Mijalkov
Karolinska Institutet
Daniel Vereb
Karolinska Institutet
Yu-Wei Chang
Göteborgs universitet
Joana B. Pereira
Karolinska Institutet
Damian Matuszewski
Uppsala universitet
Gustaf Kylberg
VINNOVA
Ida-Maria Sintorn
VINNOVA
Uppsala universitet
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
Turun Yliopisto
Åbo Akademi
Ricardo Henriques
Instituto Gulbenkian de Ciência (IGC)
University College London (UCL)
Wei Ouyang
Kungliga Tekniska Högskolan (KTH)
Trang Le
Stanford University
Estibaliz Gomez-de-Mariscal
Universidade NOVA de Lisboa
Instituto Gulbenkian de Ciência (IGC)
Daniel Sage
Ecole Polytechnique Federale de Lausanne (EPFL)
Arrate Munoz-Barrutia
Universidad Carlos III de Madrid
Gregorio Maranon Health Research Institute
Ebba Josefson Lindqvist
AI Sweden
Johanna Bergman
AI Sweden
JPhys Photonics
25157647 (eISSN)
Vol. 8 1 012501Ämneskategorier (SSIF 2025)
Medicinsk bildvetenskap
DOI
10.1088/2515-7647/ae0fd1