ELSC News

Article of the Month, April 2018 (Soreq's lab)

April 11, 2018

Intensify3D: Normalizing signal intensity in large heterogenic image stacks

Authors

  • Nadav Yayon
  • Amir Dudai
  • Nora Vrieler 
  • Oren Amsalem
  • Michael London
  • Hermona Soreq
  • Published in Nature Scientific Reports on March 2018.

    AOM 042018 soreq fig2

     

    Data generated from biological or neuroscience assays such as RNA\protein expression, physiological recordings, etc. is routinely subjected to internal normalization or filtering to reduce variability within and between samples. Our study implemented such corrections for 3D fluorescence imaging. We developed a novel algorithm, Intensify3D that enables normalization strategies for fluorescent image signals via implementing a comprehensive definition of signal and background. This fast, experimenter-based tool is amenable for use with large scale imaging datasets from all commonly used platforms -confocal, 2-Photon and Light-Sheet microscopes. It corrects heterogeneities in the signal, based on changes in the image background across all 3 dimensions as demonstrated here with or without normalization. This facilitates visualization and, more importantly, enables accurate quantification of fluorescent signals, avoids common errors and can potentially add extractable information to numerous imaging studies. 

     

    AOM 042018 soreq fig1