Detection and tracking protein molecules in fluorescence microscopic video

Kensho Fujisaki, Ayumi Hamano, Kenta Aoki, Yaokai Feng, Seiichi Uchida, Masahiko Araseki, Yuki Saito, Toshiharu Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This paper provides a bioimage informatics system of detecting and tracking protein molecules, called APP-GFPs, in a live-cell video captured by a fluorescent microscope. Since both processes encounter many difficulties such as many targets, less appearance information, and heavy background noise, we will try to design the system as robust as possible. Specifically, for the detection, a machine learning-based method is employed. For tracking, a method based on a global optimization strategy is newly developed. Experimental results showed that the speed and direction distributions of molecular motion by the proposed system were very similar to that by manual inspection.

Original languageEnglish
Title of host publicationProceedings - 2013 1st International Symposium on Computing and Networking, CANDAR 2013
Pages270-274
Number of pages5
DOIs
Publication statusPublished - Dec 1 2013
Event2013 1st International Symposium on Computing and Networking, CANDAR 2013 - Matsuyama, Ehime, Japan
Duration: Dec 4 2013Dec 6 2013

Publication series

NameProceedings - 2013 1st International Symposium on Computing and Networking, CANDAR 2013

Other

Other2013 1st International Symposium on Computing and Networking, CANDAR 2013
CountryJapan
CityMatsuyama, Ehime
Period12/4/1312/6/13

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Cite this

Fujisaki, K., Hamano, A., Aoki, K., Feng, Y., Uchida, S., Araseki, M., ... Suzuki, T. (2013). Detection and tracking protein molecules in fluorescence microscopic video. In Proceedings - 2013 1st International Symposium on Computing and Networking, CANDAR 2013 (pp. 270-274). [6726909] (Proceedings - 2013 1st International Symposium on Computing and Networking, CANDAR 2013). https://doi.org/10.1109/CANDAR.2013.47