File:Automated-Filtering-of-Intrinsic-Movement-Artifacts-during-Two-Photon-Intravital-Microscopy-pone.0053942.s015.ogv

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Automated-Filtering-of-Intrinsic-Movement-Artifacts-during-Two-Photon-Intravital-Microscopy-pone.0053942.s015.ogv (Ogg Theora video file, length 34 s, 640 × 360 pixels, 886 kbps, file size: 3.55 MB)

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English: Filtering for movement artifacts and improvement of the signal-to-noise ratio of an in vivo time-lapse video of the mouse lumbar spinal cord taken through a spinal cord window preparation. The original video (left panel) is compared with a video processed by Kalman filtering (right panel). As illustrated here, the Kalman filter option is particularly useful when the noise is predominant in the video, and when objects don’t move too fast from frame to frame. Using the Kalman filter in movies showing fast moving objects may generate motion blur artifacts. The chronic spinal cord window chamber was implemented based on the method of Farrar et al. (2012).
Date
Source Video S9 from Soulet D, Paré A, Coste J, Lacroix S (2013). "Automated Filtering of Intrinsic Movement Artifacts during Two-Photon Intravital Microscopy". PLOS ONE. DOI:10.1371/journal.pone.0053942. PMID 23326545. PMC: 3543396.
Author Soulet D, Paré A, Coste J, Lacroix S
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This file was published in a Public Library of Science journal. Their website states that the content of all PLOS journals is published under the Creative Commons Attribution 4.0 license (or its previous version depending on the publication date), unless indicated otherwise.
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Date/TimeThumbnailDimensionsUserComment
current22:41, 21 January 201334 s, 640 × 360 (3.55 MB)Open Access Media Importer Bot (talk | contribs)Automatically uploaded media file from Open Access source. Please report problems or suggestions here.

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Format Bitrate Download Status Encode time
VP9 360P 217 kbps Completed 14:58, 18 August 2018 34 s
VP9 240P 83 kbps Completed 14:58, 18 August 2018 20 s
WebM 360P 502 kbps Completed 00:35, 22 January 2013 56 s
QuickTime 144p (MJPEG) 825 kbps Completed 15:15, 16 October 2024 1.0 s

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