MIT Libraries homeMIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
  • DSpace@MIT Home
  • MIT Open Access Articles
  • MIT Open Access Articles
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Tracking of cell population from time lapse and end point confocal microscopy images with multiple hypothesis Kalman smoothing filters

Author(s)
Ong, Lee Ling; Ang, Marcelo H.; Asada, Harry
Thumbnail
DownloadAsada_Tracking of cell.pdf (3.595Mb)
PUBLISHER_POLICY

Publisher Policy

Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

Terms of use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Metadata
Show full item record
Abstract
This paper describes an automated visual tracking system combining time-lapse and end-point confocal microscopy to aid the interpretations of cell behaviors and interactions, with the focus on understanding the sprouting mechanism during angiogenesis. These multiple cells exhibit stochastic motion and are subjected to photo-bleaching and the images acquired are of low signal to noise ratio. Hence, following time-lapse imaging, high resolution end-point images are acquired. Our approach applies a probabilistic motion filter (a backward Kalman filtering followed by track smoothing) which incorporates end-point and all available time-lapse information in a mathematically consistent manner to obtain trajectory and phenotype information of multiple individual cells simultaneously. An extension of this algorithm, track smoothing with a Multiple Hypothesis Testing (MHT) data association, is proposed to improve association of multiple close contact and proliferating cells across images acquired from different time points to existing track trajectories. Our methodology was applied to tracking endothelial cell sprouting in three-dimensional micro-fluidic devices.
Date issued
2010-08
URI
http://hdl.handle.net/1721.1/77090
Department
Massachusetts Institute of Technology. Department of Mechanical Engineering; Singapore-MIT Alliance in Research and Technology (SMART)
Journal
Proceedings of the 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops, (CVPRW)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Ong, Lee-Ling S., Marcelo H. Ang, and H. Harry Asada. “Tracking of Cell Population from Time Lapse and End Point Confocal Microscopy Images with Multiple Hypothesis Kalman Smoothing Filters.” 23rd IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, (CVPRW), San Francisco, USA. June 13-18, 2010. IEEE, 2010. 71–78. Web. ©2010 IEEE.
Version: Final published version
Other identifiers
INSPEC Accession Number: 11466659
ISBN
978-1-4244-7029-7
ISSN
2160-7508

Collections
  • MIT Open Access Articles

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries homeMIT Libraries logo

Find us on

Twitter Facebook Instagram YouTube RSS

MIT Libraries navigation

SearchHours & locationsBorrow & requestResearch supportAbout us
PrivacyPermissionsAccessibility
MIT
Massachusetts Institute of Technology
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.