| First Author | Hattori R | Year | 2022 |
| Journal | Cell Rep Methods | Volume | 2 |
| Issue | 5 | Pages | 100205 |
| PubMed ID | 35637910 | Mgi Jnum | J:348903 |
| Mgi Id | MGI:7644023 | Doi | 10.1016/j.crmeth.2022.100205 |
| Citation | Hattori R, et al. (2022) PatchWarp: Corrections of non-uniform image distortions in two-photon calcium imaging data by patchwork affine transformations. Cell Rep Methods 2(5):100205 |
| abstractText | 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. |
