Toward Robust Fully 3D Filopodium Segmentation and Tracking in Time-Lapse Fluorescence Microscopy.

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Authors Martin Maska, Tereza Necasova, David Wiesner, Dmitry V. Sorokin, Igor Peterlik, Vladimir Ulman, David Svoboda
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Last Authors David Svoboda
Conference Proceedings Volume Title 2019 IEEE International Conference on Image Processing : proceedings : September 22-25, 2019, Taipei International Convention Center (TICC), Taipei, Taiwan
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Conference Name 26th IEEE International Conference on Image Processing (ICIP)
Conference Location Taipei, Taiwan
Conference Start Date 2019-09-22
Conference End Date 2019-09-25
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Publisher IEEE
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ISBN 978-1-5386-6249-6
First Page 819
Last Page 823
Print Publication Date 2019-09-26
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Abstract Development, parameter tuning, and objective benchmarking of bioimage analysis workflows heavily rely on the availability of diverse bioimage datasets accompanied by reference annotations. In this paper, we present a new benchmark dataset, FiloData3D, designed for in-depth performance assessments of fully 3D filopodium segmentation and tracking algorithms that emerged recently in the field. It consists of 180 synthetic, fully annotated, 3D time-lapse sequences of single lung cancer cells, combining different cell shapes, signal-to-noise ratios, and anisotropy ratios, which are the well-known factors that influence the quality of segmentation and tracking results. Using FiloData3D, we show that the number of filopodia and their lengths extracted are significantly underestimated in the case of traditional 2D protocols that prevail in daily practice compared to fully 3D measurements, calling for a procedural change in filopodial analyses of 3D+t bioimage data.
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DOI 10.1109/ICIP.2019.8803721
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Created By thuem
Added Date 2020-04-22
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Last Edited Date 2020-05-19 14:24:51.645
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