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An integrated platform to facilitate the calculation,validation and visualization of optical flow velocities in biological images
Authors:Xianbin Yong  Cheng-Kuang Huang  Chwee Teck Lim
Affiliation:1.Integrative Sciences and Engineering Programme, NUS Graduate School, National University of Singapore, Singapore;2.Department of Biomedical Engineering, National University of Singapore, Singapore;3.Mechanobiology Institute, National University of Singapore, Singapore;4.Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, Singapore
Abstract:Optical flow algorithms have seen poor adoption in the biological community compared with particle image velocimetry for quantifying cellular dynamics because of the lack of proper validation and an intuitive user interface. To address these challenges, we present OpFlowLab, an integrated platform that integrates our motion estimation workflow. Using routines in our workflow, we demonstrate that optical flow algorithms are more accurate than PIV in simulated images of the movement of nuclei. Qualitative assessment with actual nucleus images further supported this finding. Additionally, we show that refinement of the optical flow velocities is possible with a simple object-matching procedure, opening up the possibility of obtaining reasonable velocity estimates under less ideal imaging conditions. To visualize velocity fields, we employ artificial tracers to allow for the drawing of pathlines. Through the adoption of OpFlowLab, we are confident that optical flow algorithms will allow for the exploration of dynamic biological systems in greater accuracy and detail.
Keywords:optical flow   particle image velocimetry   collective cell migration   motion estimation
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