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Robust Plant Cell Tracking in Fluorescence Microscopy 3D+T Series
Automatic tracking of cell deformation during development using time-lapse confocal microscopy is a challenging task. In plant cell tissues, large deformations and several division cycles can occur be-tween two consecutive time-points making the image registration and tracking procedure particularly...
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creator | Petit, Manuel Cerutti, Guillaume Godin, Christophe Malandain, Gregoire |
description | Automatic tracking of cell deformation during development using time-lapse confocal microscopy is a challenging task. In plant cell tissues, large deformations and several division cycles can occur be-tween two consecutive time-points making the image registration and tracking procedure particularly difficult. Here, we propose an iterative approach where an initial registration transformation and cell-to-cell mapping are alternatively refined using high-confidence associations selected on the basis of a geometric context preservation score. The method, evaluated on a long time-lapse series of floral meristem, clearly demonstrates its superiority over a non-iterative approach. In addition, we show that the geometric context preservation score can be used to define a lineage quality assessment metric that makes it possible for an expert to provide locally nudges to finalize the lineage detection if necessary in a semi-automatic way. |
doi_str_mv | 10.1109/ISBI52829.2022.9761521 |
format | conference_proceeding |
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In plant cell tissues, large deformations and several division cycles can occur be-tween two consecutive time-points making the image registration and tracking procedure particularly difficult. Here, we propose an iterative approach where an initial registration transformation and cell-to-cell mapping are alternatively refined using high-confidence associations selected on the basis of a geometric context preservation score. The method, evaluated on a long time-lapse series of floral meristem, clearly demonstrates its superiority over a non-iterative approach. 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In plant cell tissues, large deformations and several division cycles can occur be-tween two consecutive time-points making the image registration and tracking procedure particularly difficult. Here, we propose an iterative approach where an initial registration transformation and cell-to-cell mapping are alternatively refined using high-confidence associations selected on the basis of a geometric context preservation score. The method, evaluated on a long time-lapse series of floral meristem, clearly demonstrates its superiority over a non-iterative approach. In addition, we show that the geometric context preservation score can be used to define a lineage quality assessment metric that makes it possible for an expert to provide locally nudges to finalize the lineage detection if necessary in a semi-automatic way.</abstract><pub>IEEE</pub><doi>10.1109/ISBI52829.2022.9761521</doi><tpages>4</tpages></addata></record> |
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ispartof | 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI), 2022, p.1-4 |
issn | 1945-8452 |
language | eng |
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source | IEEE Xplore All Conference Series |
subjects | cell tracking Ethics Fluorescence Fluorescence microscopy Image registration Image segmentation Measurement meristem Microscopy morphogenesis plant Quality assessment |
title | Robust Plant Cell Tracking in Fluorescence Microscopy 3D+T Series |
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