Content-aware frame interpolation (CAFI): deep learning-based temporal super-resolution for fast bioimaging.

Journal: Nature methods
PMID: 38238557

Abstract

The development of high-resolution microscopes has made it possible to investigate cellular processes in 3D and over time. However, observing fast cellular dynamics remains challenging because of photobleaching and phototoxicity. Here we report the implementation of two content-aware frame interpolation (CAFI) deep learning networks, Zooming SlowMo and Depth-Aware Video Frame Interpolation, that are highly suited for accurately predicting images in between image pairs, therefore improving the temporal resolution of image series post-acquisition. We show that CAFI is capable of understanding the motion context of biological structures and can perform better than standard interpolation methods. We benchmark CAFI's performance on 12 different datasets, obtained from four different microscopy modalities, and demonstrate its capabilities for single-particle tracking and nuclear segmentation. CAFI potentially allows for reduced light exposure and phototoxicity on the sample for improved long-term live-cell imaging. The models and the training and testing data are available via the ZeroCostDL4Mic platform.

Authors

  • Martin Priessner
    Department of Chemistry, Imperial College London, London, UK. martin.priessner@gmail.com.
  • David C A Gaboriau
    Facility for Imaging by Light Microscopy, NHLI, Imperial College London, London, UK.
  • Arlo Sheridan
  • Tchern Lenn
    CRUK City of London Centre, UCL Cancer Institute, London, UK.
  • Carlos Garzon-Coral
    Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Alexander R Dunn
    Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
  • Jonathan R Chubb
    Laboratory for Molecular Cell Biology, University College London, London, UK.
  • Aidan M Tousley
    Department of Chemical Engineering, Stanford University, Stanford, CA, USA.
  • Robbie G Majzner
    Department of Chemical Engineering, Stanford University, Stanford, CA, USA.
  • Uri Manor
    Waitt Advanced Biophotonics Center, Salk Institute for Biological Studies, La Jolla, CA, USA. umanor@salk.edu.
  • Ramon Vilar
    Department of Chemistry, Imperial College London, London, UK.
  • Romain F Laine
    Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, United Kingdom.

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