Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells

Eero Lihavainen; Jarno Mäkelä; Johannes N. Spelbrink; Andre S. Ribeiro

doi:10.1007/978-3-319-23234-8_34

Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells

Eero Lihavainen, Jarno Mäkelä, Johannes N. Spelbrink, Andre S. Ribeiro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

We present a method for automatically detecting the tips of fluorescently labeled mitochondria. The method is based on a Random Forest classifier, which is trained on small patches extracted from confocal microscope images of U2OS human osteosarcoma cells. We then adopt a particle tracking framework for tracking the detected tips, and quantify the tracking accuracy on simulated data. Finally, from images of U2OS cells, we quantify changes in mitochondrial mobility in response to the disassembly of microtubules via treatment with Nocodazole. The results show that our approach provides efficient tracking of the tips of mitochondria, and that it enables the detection of disease-associated changes in mitochondrial motility.

Original language	English
Title of host publication	Image Analysis and Processing — ICIAP 2015
Subtitle of host publication	18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II
Publisher	Springer Verlag
Pages	363-372
Number of pages	10
Volume	9280
ISBN (Print)	9783319232331
DOIs	https://doi.org/10.1007/978-3-319-23234-8_34
Publication status	Published - 2015
Publication type	A4 Article in conference proceedings
Event	International Conference on Image Analysis and Processing - Duration: 1 Jan 1900 → …

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9280
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Image Analysis and Processing
Period	1/01/00 → …

Keywords

Detection
Image analysis
Mitochondria
Tracking

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Computer Science(all)
Theoretical Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-319-23234-8_34

Cite this

Lihavainen, E., Mäkelä, J., Spelbrink, J. N., & Ribeiro, A. S. (2015). Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells. In Image Analysis and Processing — ICIAP 2015: 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II (Vol. 9280, pp. 363-372). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9280). Springer Verlag. https://doi.org/10.1007/978-3-319-23234-8_34

Lihavainen, Eero ; Mäkelä, Jarno ; Spelbrink, Johannes N. et al. / Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells. Image Analysis and Processing — ICIAP 2015: 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II. Vol. 9280 Springer Verlag, 2015. pp. 363-372 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{b97da5a8c7bc4e97a14704c15d2b360c,

title = "Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells",

abstract = "We present a method for automatically detecting the tips of fluorescently labeled mitochondria. The method is based on a Random Forest classifier, which is trained on small patches extracted from confocal microscope images of U2OS human osteosarcoma cells. We then adopt a particle tracking framework for tracking the detected tips, and quantify the tracking accuracy on simulated data. Finally, from images of U2OS cells, we quantify changes in mitochondrial mobility in response to the disassembly of microtubules via treatment with Nocodazole. The results show that our approach provides efficient tracking of the tips of mitochondria, and that it enables the detection of disease-associated changes in mitochondrial motility.",

keywords = "Detection, Image analysis, Mitochondria, Tracking",

author = "Eero Lihavainen and Jarno M{\"a}kel{\"a} and Spelbrink, {Johannes N.} and Ribeiro, {Andre S.}",

year = "2015",

doi = "10.1007/978-3-319-23234-8_34",

language = "English",

isbn = "9783319232331",

volume = "9280",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "363--372",

booktitle = "Image Analysis and Processing — ICIAP 2015",

address = "Germany",

note = "International Conference on Image Analysis and Processing ; Conference date: 01-01-1900",

}

Lihavainen, E, Mäkelä, J, Spelbrink, JN & Ribeiro, AS 2015, Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells. in Image Analysis and Processing — ICIAP 2015: 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II. vol. 9280, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9280, Springer Verlag, pp. 363-372, International Conference on Image Analysis and Processing, 1/01/00. https://doi.org/10.1007/978-3-319-23234-8_34

Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells. / Lihavainen, Eero; Mäkelä, Jarno; Spelbrink, Johannes N. et al.
Image Analysis and Processing — ICIAP 2015: 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II. Vol. 9280 Springer Verlag, 2015. p. 363-372 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9280).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells

AU - Lihavainen, Eero

AU - Mäkelä, Jarno

AU - Spelbrink, Johannes N.

AU - Ribeiro, Andre S.

PY - 2015

Y1 - 2015

N2 - We present a method for automatically detecting the tips of fluorescently labeled mitochondria. The method is based on a Random Forest classifier, which is trained on small patches extracted from confocal microscope images of U2OS human osteosarcoma cells. We then adopt a particle tracking framework for tracking the detected tips, and quantify the tracking accuracy on simulated data. Finally, from images of U2OS cells, we quantify changes in mitochondrial mobility in response to the disassembly of microtubules via treatment with Nocodazole. The results show that our approach provides efficient tracking of the tips of mitochondria, and that it enables the detection of disease-associated changes in mitochondrial motility.

AB - We present a method for automatically detecting the tips of fluorescently labeled mitochondria. The method is based on a Random Forest classifier, which is trained on small patches extracted from confocal microscope images of U2OS human osteosarcoma cells. We then adopt a particle tracking framework for tracking the detected tips, and quantify the tracking accuracy on simulated data. Finally, from images of U2OS cells, we quantify changes in mitochondrial mobility in response to the disassembly of microtubules via treatment with Nocodazole. The results show that our approach provides efficient tracking of the tips of mitochondria, and that it enables the detection of disease-associated changes in mitochondrial motility.

KW - Detection

KW - Image analysis

KW - Mitochondria

KW - Tracking

U2 - 10.1007/978-3-319-23234-8_34

DO - 10.1007/978-3-319-23234-8_34

M3 - Conference contribution

AN - SCOPUS:84944768777

SN - 9783319232331

VL - 9280

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 363

EP - 372

BT - Image Analysis and Processing — ICIAP 2015

PB - Springer Verlag

T2 - International Conference on Image Analysis and Processing

Y2 - 1 January 1900

ER -

Lihavainen E, Mäkelä J, Spelbrink JN, Ribeiro AS. Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells. In Image Analysis and Processing — ICIAP 2015: 18th International Conference, Genoa, Italy, September 7-11, 2015, Proceedings, Part II. Vol. 9280. Springer Verlag. 2015. p. 363-372. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23234-8_34

Detecting and tracking the tips of fluorescently labeled mitochondria in U2OS cells

Abstract

Publication series

Conference

Keywords

Publication forum classification

ASJC Scopus subject areas

UN SDGs

Access to Document

Fingerprint

Cite this