A spatio-temporally compensated acousto-optic scanner for two-photon microscopy providing large field of view

Recent advances in microscopy and optics, computer sciences, and the available fluorophores used to label molecules of interest have empowered investigators to utilize intravital two-photon microscopy to study the dynamic events within the functioning kidney. This emerging technique enables investigators to follow functional and structural alterations with subcellular resolution within the same field of view over seconds to weeks. This approach invigorates the validity of data and facilitates analysis and interpretation as trends are more readily determined when one is more closely monitoring indicative physiological parameters. Therefore, in this review we emphasize how specific approaches will enable studies into glomerular permeability, proximal tubule endocytosis, and microvascular function within the kidney. We attempt to show how visual data can be quantified, thus allowing enhanced understanding of the process under study. Finally, emphasis is given to the possible future opportunities of this technology and its present limitations.

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NoRMCorre: An online algorithm for piecewise rigid motion correction of calcium imaging data

10.1101/108514 ◽

2017 ◽

Cited By ~ 8

Author(s):

Eftychios A. Pnevmatikakis ◽

Andrea Giovannucci

Keyword(s):

Calcium Imaging ◽

Motion Correction ◽

Rigid Motion ◽

Motion Artifacts ◽

Streaming Data ◽

Field Of View ◽

Large Field ◽

Motion Field ◽

Imaging Data ◽

Two Photon

AbstractBackgroundMotion correction is a challenging pre-processing problem that arises early in the analysis pipeline of calcium imaging data sequences. The motion artifacts in two-photon microscopy recordings can be non-rigid, arising from the finite time of raster scanning and non-uniform deformations of the brain medium.New methodWe introduce an algorithm for fast Non-Rigid Motion Correction (NoRMCorre) based on template matching. NoRMCorre operates by splitting the field of view into overlapping spatial patches that are registered at a sub-pixel resolution for rigid translation against a continuously updated template. The estimated alignments are subsequently up-sampled to create a smooth motion field for each frame that can efficiently approximate non-rigid motion in a piecewise-rigid manner.Existing methodsExisting approaches either do not scale well in terms of computational performance or are targeted to motion artifacts arising from low speed scanning, whereas modern datasets with large field of view are more prone to non-rigid brain deformation issues.ResultsNoRMCorre can be run in an online mode resulting in comparable to or even faster than real time motion registration on streaming data. We evaluate the performance of the proposed method with simple yet intuitive metrics and compare against other non-rigid registration methods on two-photon calcium imaging datasets. Open source Matlab and Python code is also made available.ConclusionsThe proposed method and code provide valuable support to the community for solving large scale image registration problems in calcium imaging, especially when non-rigid deformations are present in the acquired data.

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