CellTrackVis: Analyzing the Performance of Cell Tracking Algorithms
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Live-cell imaging is a common data acquisition technique used by biologists to analyze cell behavior. Since manually tracking cells in a video sequence is extremely time-consuming, many automatic algorithms have been developed in the last twenty years to accomplish the task. However, none of these algorithms can yet claim robust tracking performance at the varying of acquisition conditions (e.g., cell type, acquisition device, cell treatments). While many visualization tools exist to help with cell behavior analysis, there are no tools to help with the algorithm's validation. This paper proposes CellTrackVis, a new visualization tool for evaluating cell tracking algorithms. CellTrackVis allows comparing automatically generated cell tracks with ground truth data to help biologists select the best-suited algorithm for their experimental pipeline. Moreover, CellTackVis can be used as a debugging tool while developing a new cell tracking algorithm to investigate where, when, and why each tracking error occurred.
Description
CCS Concepts: Applied computing --> Bioinformatics; Human-centered computing --> Visualization toolkits
@inproceedings{10.2312:evs.20221103,
booktitle = {EuroVis 2022 - Short Papers},
editor = {Agus, Marco and Aigner, Wolfgang and Hoellt, Thomas},
title = {{CellTrackVis: Analyzing the Performance of Cell Tracking Algorithms}},
author = {Li, Weimin and Zhang, Xiang and Stern, Alan and Birtwistle, Marc and Iuricich, Federico},
year = {2022},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-184-7},
DOI = {10.2312/evs.20221103}
}