PatchWarp: Corrections of non-uniform image distortions in two-photon calcium imaging data by patchwork affine transformations

Cell Rep Methods. 2022 Apr 27;2(5):100205. doi: 10.1016/j.crmeth.2022.100205. eCollection 2022 May 23.

Abstract

Complex distortions on calcium imaging often impair image registration accuracy. Here, we developed a registration algorithm, PatchWarp, to robustly correct slow image distortion for calcium imaging data. PatchWarp is a two-step algorithm with rigid and non-rigid image registrations. To correct non-uniform image distortions, it splits the imaging field and estimates the best affine transformation matrix for each of the subfields. The distortion-corrected subfields are stitched together like a patchwork to reconstruct the distortion-corrected imaging field. We show that PatchWarp robustly corrects image distortions of calcium imaging data collected from various cortical areas through glass window or gradient-index (GRIN) lens with a higher accuracy than existing non-rigid algorithms. Furthermore, it provides a fully automated method of registering images from different imaging sessions for longitudinal neural activity analyses. PatchWarp improves the quality of neural activity analyses and is useful as a general approach to correct image distortions in a wide range of disciplines.

Keywords: affine transformation; calcium imaging; image distortion; image registration; longitudinal imaging; motion correction; multi-photon; non-rigid registration; two photon; warp correction.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms*
  • Calcium, Dietary
  • Image Enhancement* / methods

Substances

  • Calcium, Dietary

Associated data

  • figshare/10.6084/m9.figshare.19212501.v1
  • figshare/10.6084/m9.figshare.19217421.v1