Automatic tracking of multiple zebrafish larvae with resilience against segmentation errors

Wang, X; Cheng, E; Burnett, IS; Wilkinson, R; Lech, M

Automatic tracking of multiple zebrafish larvae with resilience against segmentation errors

Wang, X Cheng, E

Burnett, IS

Wilkinson, R Lech, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Symposium on Biomedical Imaging, 2018, 2018-April pp. 1157 - 1160
Issue Date:: 2018-05-23

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Field	Value	Language
dc.contributor.author	Wang, X	en_US
dc.contributor.author	Cheng, E https://orcid.org/0000-0003-1632-8062	en_US
dc.contributor.author	Burnett, IS https://orcid.org/0000-0003-3795-7722	en_US
dc.contributor.author	Wilkinson, R	en_US
dc.contributor.author	Lech, M	en_US
dc.date.issued	2018-05-23	en_US
dc.identifier.citation	Proceedings - International Symposium on Biomedical Imaging, 2018, 2018-April pp. 1157 - 1160	en_US
dc.identifier.isbn	9781538636367	en_US
dc.identifier.issn	1945-7928	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133758
dc.description.abstract	© 2018 IEEE. The accurate tracking of zebrafish larvae movement is essential to many biomedical and neural science applications. This paper develops an accurate and reliable multiple zebrafish larvae tracking system resilient to detection and segmentation errors due to object misdetection and occlusion. The proposed system can therefore be applied to microscopic videos in unconstrained, realistic imaging conditions. Evaluated on a set of single and multiple adult and larvae zebrafish videos, a wide variety of (complex) video conditions were tested, including shadowing, labels, water bubbles and background artefacts. The proposed system obtains decreased overall MOTP error of up to 44.49 pixels compared to the commercial LoliTrack system, and increased MOTA accuracy by 31.57% compared with the state-of-the-art idTracker approach. The results offer an additional advantage of improved position detection, increased accuracy and unique identification compared to current techniques.	en_US
dc.relation.ispartof	Proceedings - International Symposium on Biomedical Imaging	en_US
dc.relation.isbasedon	10.1109/ISBI.2018.8363776	en_US
dc.title	Automatic tracking of multiple zebrafish larvae with resilience against segmentation errors	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2018-April	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Professional Practice and Leadership
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2018-April	en_US

Abstract:

© 2018 IEEE. The accurate tracking of zebrafish larvae movement is essential to many biomedical and neural science applications. This paper develops an accurate and reliable multiple zebrafish larvae tracking system resilient to detection and segmentation errors due to object misdetection and occlusion. The proposed system can therefore be applied to microscopic videos in unconstrained, realistic imaging conditions. Evaluated on a set of single and multiple adult and larvae zebrafish videos, a wide variety of (complex) video conditions were tested, including shadowing, labels, water bubbles and background artefacts. The proposed system obtains decreased overall MOTP error of up to 44.49 pixels compared to the commercial LoliTrack system, and increased MOTA accuracy by 31.57% compared with the state-of-the-art idTracker approach. The results offer an additional advantage of improved position detection, increased accuracy and unique identification compared to current techniques.

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http://hdl.handle.net/10453/133758