Segmenting and tracking multiple dividing targets using ilastik

• Verfasst von: Haubold, Carsten [VerfasserIn]
• Verfasst von: Schiegg, Martin [VerfasserIn]
• Verfasst von: Kreshuk, Anna [VerfasserIn]
• Verfasst von: Berg, Stuart [VerfasserIn]
• Verfasst von: Köthe, Ullrich [VerfasserIn]
• Verfasst von: Hamprecht, Fred [VerfasserIn]
• Titel: Segmenting and tracking multiple dividing targets using ilastik
• Verf.angabe: Carsten Haubold, Martin Schiegg, Anna Kreshuk, Stuart Berg, Ullrich Koethe, Fred A. Hamprecht
• E-Jahr: 2016
• Jahr: 21 May 2016
• Umfang: 11 S.
• Fussnoten: Gesehen am 03.06.2020
• Titel Quelle: Enthalten in: Focus on bio-image informatics
• Ort Quelle: Cham : Springer, 2016
• Jahr Quelle: 2016
• Band/Heft Quelle: (2016), Seite 219-229
• ISBN Quelle: 978-3-319-28549-8
• DOI: doi:10.1007/978-3-319-28549-8_8
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Division Classifier
• Sach-SW: Probable Configuration
• Sach-SW: Tracking Algorithm
• Sach-SW: Tracking Optimization
• Sach-SW: Tracking Result
• K10plus-PPN: 1699271380

Abstract

Tracking crowded cells or other targets in biology is often a challenging task due to poor signal-to-noise ratio, mutual occlusion, large displacements, little discernibility, and the ability of cells to divide. We here present an open source implementation of conservation tracking (Schiegg et al., IEEE international conference on computer vision (ICCV). IEEE, New York, pp 2928-2935, 2013) in the ilastik software framework. This robust tracking-by-assignment algorithm explicitly makes allowance for false positive detections, undersegmentation, and cell division. We give an overview over the underlying algorithm and parameters, and explain the use for a light sheet microscopy sequence of a Drosophila embryo. Equipped with this knowledge, users will be able to track targets of interest in their own data.