Correction for non-rigid movement artefacts in calcium imaging using local-global optical flow and PCA-based templates
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Correction for non-rigid movement artefacts in calcium imaging using local-global optical flow and PCA-based templates. / Brazhe, A.; Fordsmann, J.; Lauritzen, M.
In: Journal of Cerebral Blood Flow and Metabolism, Vol. 37, No. S1, PS04-077, 04.2017, p. 360-361.Research output: Contribution to journal › Conference abstract in journal › Research › peer-review
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TY - ABST
T1 - Correction for non-rigid movement artefacts in calcium imaging using local-global optical flow and PCA-based templates
AU - Brazhe, A.
AU - Fordsmann, J.
AU - Lauritzen, M.
PY - 2017/4
Y1 - 2017/4
N2 - Objectives: Correction for lateral displacements of the imaged area is often a necessary first step of processing calcium imaging data, especially in awake animal studies. We address two problems: (1) image displacements (warps) can be poorly described by simple rigid-body translations or shifts and can be non-uniform across image; (2) due to fluorescence intensity changes single template image may not be optimal for a subset of the movie frames.Methods: We address the first problem by using either a combined local/global algorithm of optical flow estimation or an original algorithm based on calculation of optical flow in image patches with global regularization. Both algorithms estimate smooth optical flow fields between a current image and a template image and allow for correction of large-scale displacements by employing a multiscale pyramidal approach. The second problem is solved by using a set of template images, obtained from clusters of image frames in low-dimensional PCA-based space. To allow for efficient storage of the estimated image warps, they can be represented as low-pass DCT coefficients or by other dictionary-based methods.Conclusions: The proposed pipeline for motion correction of calcium timelapse imaging data is accurate, can represent non-rigid image distortions, robust to noisy data and allows for fast registration of large videos. The implementation is open-source and is programmed in Python, which provides for easy access and merging into downstream image processing workflows.
AB - Objectives: Correction for lateral displacements of the imaged area is often a necessary first step of processing calcium imaging data, especially in awake animal studies. We address two problems: (1) image displacements (warps) can be poorly described by simple rigid-body translations or shifts and can be non-uniform across image; (2) due to fluorescence intensity changes single template image may not be optimal for a subset of the movie frames.Methods: We address the first problem by using either a combined local/global algorithm of optical flow estimation or an original algorithm based on calculation of optical flow in image patches with global regularization. Both algorithms estimate smooth optical flow fields between a current image and a template image and allow for correction of large-scale displacements by employing a multiscale pyramidal approach. The second problem is solved by using a set of template images, obtained from clusters of image frames in low-dimensional PCA-based space. To allow for efficient storage of the estimated image warps, they can be represented as low-pass DCT coefficients or by other dictionary-based methods.Conclusions: The proposed pipeline for motion correction of calcium timelapse imaging data is accurate, can represent non-rigid image distortions, robust to noisy data and allows for fast registration of large videos. The implementation is open-source and is programmed in Python, which provides for easy access and merging into downstream image processing workflows.
U2 - 10.1177/0271678X17695991
DO - 10.1177/0271678X17695991
M3 - Conference abstract in journal
C2 - 28366131
VL - 37
SP - 360
EP - 361
JO - Journal of Cerebral Blood Flow and Metabolism
JF - Journal of Cerebral Blood Flow and Metabolism
SN - 0271-678X
IS - S1
M1 - PS04-077
ER -
ID: 182544693