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Dataset . 2021
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Data sources: Datacite
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Dataset . 2021
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ZENODO
Dataset . 2021
License: CC BY
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ZENODO
Dataset . 2021
License: CC BY
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Tracking Data I/II of the publication "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction"

Authors: Löffler, Katharina; Scherr, Tim; Mikut, Ralf;

Tracking Data I/II of the publication "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction"

Abstract

DATA belonging to the paper "A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction" Katharina Löffler, Tim Scherr, Ralf Mikut doi: https://doi.org/10.1101/2021.03.16.435631 ----------------------------- To investigate the influence of different segmentation errors on the tracking performance we simulate errorneous segmentation data: - under-segmentation (referred to as "merge" in the folders), over-segmentation("split"), False Negatives ("remove"), combination of the aforementioned errors ("mixed") - percentages: 1,2,5,10,20 of errorneous masks per dataset - runs: 5 randomly initialized runs per combination - datasets: Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ each with two image sequences ---> in total 4 (error types) * 5 (percentage) * 5 (runs) * 2 (data sets) * 2 (image sequences) = 400 datasets The datasets can be recreated by running our code https://git.scc.kit.edu/KIT-Sch-GE/2021-cell-tracking ---------------------------- RESULTS We evuated the four tracking algorithms KIT-Sch-GE(1), KTH-SE, MU-Lux-CZ and our proposed algorithm on the aforementioned datasets and compare their performance using the CTC metrics DET, SEG and TRA. This repository contains all metrics as xls files and all tracking results as image sequences. xls files ----------- compare_all_trackers_on_synt_bm.csv Comparing the tracking algorithms MU-Lux-CZ, KTH-SE, KIT-Sch-GE(1) and the proposed tracking algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets). Reported scores are DET, SEG and TRA from the Cell Tracking Challenge (Fig8 and Fig9 and Supplementary Figures 3 and 4 are created from this data) compare_postprocessing_on_synth_bm.csv Comparing the different post-processing strategies of the proposed tracking algorithm algorithm on synthetically degraded segmentation data Fluo-N2DH-SIM+ and Fluo-N3DH-SIM+ (Cell Tracking Challenge datasets). Reported scores are DET, SEG and TRA from the Cell Tracking Challenge (Fig7 and Fig8 and Supplementary Figures 1 and 2 are created from this data) PLEASE NOTE: the folder compare_postprocessing_synth_bm is provided in the repository 10.5281/zenodo.5227610 due to size restrictions. folders (decompressed approximately 90GB of data!) ----------- tracking_data compare_all_synth_bm Contains all tracking results for each tracking algorithm on the synthetically degraded datasets () compare_all_synth_bm_no_error Contains the tracking results for each tracking algorithm provided with the perfect ground truth segmentation data compare_postprocessing_synth_bm [will be stored in 10.5281/zenodo.5227610 due to size restrictions] Contains all tracking resuls for each postprocessing configuration of the proposed cell tracking algorithm the leaf folders are names run_xPOSTPROCESSING where x is the run number and POSTPROCESSING the postprocessing key Postprocessing keys: ("no untangle" or "no masks" is indicated by an overline in the paper) all ("untangle + masks" in the paper) nd ("no untangle + masks") nd_ns-l ("no untangle + no masks") ns-l ("untangle + no masks")

Keywords

cell tracking; tracking algorithms

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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