Guest Editors

Virginie Uhlmann (European Bioinformatics Institute (EMBL-EBI), Cambridge, UK, uhlmann@ebi.ac.uk)

Daniel Sage (Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland, daniel.sage@epfl.ch)

Jong Chul Ye (Korea Advanced Institute of Science & Technology (KAIST), Daejeon, Republic of Korea, jong.ye@kaist.ac.kr)

Erik Meijering (University of New South Wales (UNSW), Sydney, Australia, erik.meijering@unsw.edu.au)

Scope

Artificial intelligence has revolutionized computer vision and its many fields of application, including bioimage informatics. Machine and deep learning in particular are being transformative in their ability to provide solutions that automate complex image analysis tasks across a wide range of different datasets, leading to a proliferation of the use of computational approaches by experimental life scientists. Beyond automation, artificial intelligence is also increasingly being used to mine visual information and reveal patterns that are too complex for the human eye to grasp, providing novel insights into the organization and dynamics of living systems. 

This special issue assembles original research articles and software reports introducing artificial intelligence approaches to bioimage informatics ranging from microscopy image processing and analysis (e.g., image restoration, object detection, segmentation, tracking) to quantification tasks (e.g., representation and metric learning). Acknowledging the strong potential of artificial intelligence approaches in bioimage informatics, we also welcome reviews, opinion pieces, and perspective articles providing overviews or outlooks on this quickly-evolving field of research.

More information for authors about article types and format can be found at https://www.cambridge.org/core/journals/biological-imaging/information/instructions-authors.

Key Dates

Submission deadline: 31 March 2024

Reviews to authors: 30 April 2024

Revision due: 15 May 2024

Final decision: 15 June 2024

Publication target: 30 June 2024