High-resolution cell imaging using white light phase shifting interferometry and iterative phase deconvolution.
Shubham TiwariShilpa TayalShivam TrivediHarpreet KaurDalip Singh MehtaPublished in: Journal of biophotonics (2024)
An optimization algorithm is presented for the deconvolution of a complex field to improve the resolution and accuracy of quantitative phase imaging (QPI). A high-resolution phase map can be recovered by solving a constrained optimization problem of deconvolution using a complex gradient operator. The method is demonstrated on phase measurements of samples using a white light based phase shifting interferometry (WLPSI) method. The application of the algorithm on real and simulated objects shows a significant resolution and contrast improvement. Experiments performed on Escherichia coli bacterium have revealed its sub-cellular structures that were not visible in the raw WLPSI images obtained using a five phase shifting method. These features can give valuable insights into the structures and functioning of biological cells. The algorithm is simple in implementation and can be incorporated into other QPI modalities .
Keyphrases
- high resolution
- escherichia coli
- deep learning
- machine learning
- magnetic resonance imaging
- mass spectrometry
- primary care
- healthcare
- stem cells
- single cell
- mesenchymal stem cells
- cystic fibrosis
- computed tomography
- pseudomonas aeruginosa
- cell death
- convolutional neural network
- contrast enhanced
- photodynamic therapy
- cell cycle arrest
- quality improvement
- klebsiella pneumoniae