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@inproceedings{1530536,
author = {Maška, Martin and Nečasová, Tereza and Wiesner, David and Sorokin, Dmitry and Peterlík, Igor and Ulman, Vladimír and Svoboda, David},
address = {Taipei},
booktitle = {26th IEEE International Conference on Image Processing},
doi = {http://dx.doi.org/10.1109/ICIP.2019.8803721},
keywords = {Benchmark dataset; synthetic image data; filopodium segmentation; filopodium tracking},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Taipei},
isbn = {978-1-5386-6249-6},
pages = {819-823},
publisher = {IEEE},
title = {Toward Robust Fully 3D Filopodium Segmentation and Tracking in Time-Lapse Fluorescence Microscopy},
url = {https://doi.org/10.1109/ICIP.2019.8803721},
year = {2019}
}
TY - JOUR
ID - 1530536
AU - Maška, Martin - Nečasová, Tereza - Wiesner, David - Sorokin, Dmitry - Peterlík, Igor - Ulman, Vladimír - Svoboda, David
PY - 2019
TI - Toward Robust Fully 3D Filopodium Segmentation and Tracking in Time-Lapse Fluorescence Microscopy
PB - IEEE
CY - Taipei
SN - 9781538662496
KW - Benchmark dataset
KW - synthetic image data
KW - filopodium segmentation
KW - filopodium tracking
UR - https://doi.org/10.1109/ICIP.2019.8803721
N2 - 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.
ER -
MAŠKA, Martin, Tereza NEČASOVÁ, David WIESNER, Dmitry SOROKIN, Igor PETERLÍK, Vladimír ULMAN and David SVOBODA. Toward Robust Fully 3D Filopodium Segmentation and Tracking in Time-Lapse Fluorescence Microscopy. Online. In \textit{26th IEEE International Conference on Image Processing}. Taipei: IEEE, 2019, p.~819-823. ISBN~978-1-5386-6249-6. Available from: https://dx.doi.org/10.1109/ICIP.2019.8803721.
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