Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00095219" target="_blank" >RIV/00216224:14330/17:00095219 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1109/ICCVW.2017.8" target="_blank" >http://dx.doi.org/10.1109/ICCVW.2017.8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICCVW.2017.8" target="_blank" >10.1109/ICCVW.2017.8</a>

Result language

angličtina

Original language name

Particle Tracking Accuracy Measurement Based on Comparison of Linear Oriented Forests

Original language description

Particle tracking is of fundamental importance in diverse quantitative analyses of dynamic intracellular processes using time-lapse microscopy. Due to frequent impracticability of tracking particles manually, a number of fully automated algorithms have been developed over past decades, carrying out the tracking task in two subsequent phases: (1) particle detection and (2) particle linking. An objective benchmark for assessing the performance of such algorithms was recently established by the Particle Tracking Challenge. Because its performance evaluation protocol finds correspondences between a reference and algorithm-generated tracking result at the level of individual tracks, the performance assessment strongly depends on the algorithm linking capabilities. In this paper, we propose a novel performance evaluation protocol based on a simplified version of the tracking accuracy measure employed in the Cell Tracking Challenge, which establishes the correspondences at the level of individual particle detections, thus allowing one to evaluate the performance of each of the two phases in an isolated, unbiased manner. By analyzing the tracking results of all 14 algorithms competing in the Particle Tracking Challenge using the proposed evaluation protocol, we reveal substantial changes in their detection and linking performance, yielding rankings different from those reported previously.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GJ16-03909Y" target="_blank" >GJ16-03909Y: Development of Reliable Methods for Automated Quantitative Characterization of Cell Motility in Fluorescence Microscopy</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

16th IEEE International Conference on Computer Vision Workshops

ISBN

9781538610343

ISSN

2473-9936

e-ISSN

—

Number of pages

7

Pages from-to

11-17

Publisher name

IEEE

Place of publication

Venice

Event location

Venice, Italy

Event date

Jan 1, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000425239600002