Localization and tracking in 4D fluorescence microscopy imagery

Shahira Abousamra, Shai Adar, Natalie Elia, Roy Shilkrot

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

3D fluorescence microscopy continues to pose challenging tasks with more experiments leading to identifying new physiological patterns in cells' life cycle and activity. It then falls on the hands of biologists to annotate this imagery which is laborious and time-consuming, especially with noisy images and hard to see and track patterns. Modeling of automation tasks that can handle depth-varying light conditions and noise, and other challenges inherent in 3D fluorescence microscopy often becomes complex and requires high processing power and memory. This paper presents an efficient methodology for the localization, classification, and tracking in fluorescence microscopy imagery by taking advantage of time sequential images in 4D data. We show the application of our proposed method on the challenging task of localizing and tracking microtubule fibers' bridge formation during the cell division of zebrafish embryos where we achieve 98% accuracy and 0.94 F1-score.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
PublisherInstitute of Electrical and Electronics Engineers
Pages2371-2379
Number of pages9
ISBN (Electronic)9781538661000
DOIs
StatePublished - 13 Dec 2018
Event31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018 - Salt Lake City, United States
Duration: 18 Jun 201822 Jun 2018

Publication series

NameIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Volume2018-June
ISSN (Print)2160-7508
ISSN (Electronic)2160-7516

Conference

Conference31st Meeting of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2018
Country/TerritoryUnited States
CitySalt Lake City
Period18/06/1822/06/18

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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