An algorithm for automated detection, localization and measurement of local calcium signals from camera-based imaging

Cell Calcium. 2014 Sep;56(3):147-56. doi: 10.1016/j.ceca.2014.06.003. Epub 2014 Jun 24.


Local Ca(2+) transients such as puffs and sparks form the building blocks of cellular Ca(2+) signaling in numerous cell types. They have traditionally been studied by linescan confocal microscopy, but advances in TIRF microscopy together with improved electron-multiplied CCD (EMCCD) cameras now enable rapid (>500 frames s(-1)) imaging of subcellular Ca(2+) signals with high spatial resolution in two dimensions. This approach yields vastly more information (ca. 1 Gb min(-1)) than linescan imaging, rendering visual identification and analysis of local events imaged both laborious and subject to user bias. Here we describe a routine to rapidly automate identification and analysis of local Ca(2+) events. This features an intuitive graphical user-interfaces and runs under Matlab and the open-source Python software. The underlying algorithm features spatial and temporal noise filtering to reliably detect even small events in the presence of noisy and fluctuating baselines; localizes sites of Ca(2+) release with sub-pixel resolution; facilitates user review and editing of data; and outputs time-sequences of fluorescence ratio signals for identified event sites along with Excel-compatible tables listing amplitudes and kinetics of events.

Keywords: Algorithm; Automation; Calcium; Fluorescence; Imaging; Total internal reflection microscopy.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Automation
  • Calcium / metabolism*
  • Calcium Signaling / physiology*
  • Fluorescence
  • Humans
  • Microscopy, Fluorescence / instrumentation
  • Microscopy, Fluorescence / methods*
  • Neuroblastoma / metabolism*
  • Neuroblastoma / pathology
  • Tumor Cells, Cultured


  • Calcium