PhD proj.; Image Analysis using Deep Learning for Optical Super-resolution Microscopy of Living Samples

  • Thesis: Image Analysis using Deep Learning for Optical Super-resolution Microscopy of Living Samples
  • Supervisor 1: Prof. Clemens Kaminski, Laser Analytics Group, Cambridge University
  • Supervisor 2: Prof. Pietro Lió, Computational Biology within Artificial Intelligence Group, Cambridge University
  • Advisor: Dr Jérôme Boulanger, Senior Research at Laboratory for Molecular Biology, MRC

Imaging at high spatio-temporal resolution requires a trade-off with image quality leading to low signal-to-noise ratio in acquired data. This renders traditional image analysis methods to perform unreliably. In this thesis I propose methods for image reconstruction, denoising and segmentation using deep learning methods that are robust to noise.

Charles Nicklas Christensen
Charles Nicklas Christensen
PhD Candidate
Computer Vision & AI

My research interests include computer vision, deep learning and imaging.