Professor Pier Luigi Dragotti

Imperial College London

Computational Lightfield Microscopy

One of the key goals of neuroscience is understanding how networks of neurons in the mammalian brain process information. Achieving this goal requires the ability to capture the dynamics of large populations of neurons at high speed and resolution over a large area of the brain. The best way to image fast is by using scanless microscopes and a particularly attractive candidate for highspeed 3D imaging is light-field microscopy (LFM). In collaboration with Dr A. Foust we have built a new lightfield microscope and new computational tools that eanabled us to image large number of neurons at 100Hz and our technology promises to image large polupations of neurons at 1KHz.


Recent Talk

Main publications:

  • P. Song et al.,"Model-Based Explainable Deep Learning for Light-Field Microscopy Imaging", IEEE Transactions on Image Processing, 2024.
  • H. Verinaz et al. "Physics-based Deep Learning for Imaging Neuronal Activity via Two-photon and Light Field Microscopy", IEEE Transactions on Computational Imaging, 2023.
  • H. Verinaz-Jadan et al." Shift-Invariant-Subspace Discretization and Volume Reconstruction for Light Field Microscopy", IEEE Transactions on Computational Imaging, 2022
  • P. Song et al."Light-field Microscopy for optical imaging of neural activity: when model-based methods meet data-driven approaches" IEEE Signal Processing Magazine, vol 39 March 2022
  • P. Song P, H. Verinaz Jadan, C. Howe, P. Quicke, A. Foust and P.L. Dragotti, 3D localization for light-field microscopy via convolutional sparse coding on epipolar images, IEEE Transactions on Computational Imaging, Vol:6, pages:1017-1032, 2020.



  • Research Areas

    Wavelet theory.
    Sampling theory.
    Sparse Signal Processing
    Computational Imaging
    Data-Driven Image processing and Image Super-Resolution.