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

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 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.

Basic information

Original name

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

Authors

MAŠKA, Martin (203 Czech Republic, guarantor, belonging to the institution), Tereza NEČASOVÁ (203 Czech Republic, belonging to the institution), David WIESNER (203 Czech Republic, belonging to the institution), Dmitry SOROKIN (643 Russian Federation), Igor PETERLÍK (703 Slovakia, belonging to the institution), Vladimír ULMAN (203 Czech Republic) and David SVOBODA (203 Czech Republic, belonging to the institution)

Edition

Taipei, 26th IEEE International Conference on Image Processing, p. 819-823, 5 pp. 2019

Publisher

IEEE

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/00216224:14330/19:00107396

Organization unit

Faculty of Informatics

ISBN

978-1-5386-6249-6

ISSN

DOI

http://dx.doi.org/10.1109/ICIP.2019.8803721

UT WoS

000521828600163

Keywords in English

Benchmark dataset; synthetic image data; filopodium segmentation; filopodium tracking

Tags

cbia-web, core_B, firank_A

Tags

International impact, Reviewed

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Abstract

V originále

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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Links

EF16_013/0001775, research and development project	Name: Modernizace a podpora výzkumných aktivit národní infrastruktury pro biologické a medicínské zobrazování Czech-BioImaging
GA17-05048S, research and development project	Name: Segmentace a trekování živých buněk v multimodálních obrazech Investor: Czech Science Foundation
LTC17016, research and development project	Name: Benchmarking algoritmů segmentace a sledování buněk Investor: Ministry of Education, Youth and Sports of the CR, Benchmarking of algorithms for cell segmentation and tracking, INTER-COST
MUNI/A/1018/2018, interní kód MU	Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VIII. Investor: Masaryk University, Category A
MUNI/A/1040/2018, interní kód MU	Name: Zapojení studentů Fakulty informatiky do mezinárodní vědecké komunity 19 (Acronym: SKOMU) Investor: Masaryk University, Category A