Classification of protein localization patterns obtained via fluorescence light microscopy

Michael V. Boland, Mia K. Markey, Robert F. Murphy

Research output: Contribution to journalConference articlepeer-review

Abstract

We describe a method of classifying cellular protein localization patterns based on their appearance in fluorescence light microscope images. Images depicting cellular protein localization were obtained using immunofluorescence microscopy. After collection, the images were processed and subject to feature extraction. Zernike moments were calculated for each image and used as inputs to one of two classification schemes: a classification tree or a neural network. Of the two classifiers, the neural network demonstrated better performance, correctly classifying 84% of previously unseen images. This work has application as a novel approach to protein description, as a means of automating microscopes, and as part of a new approach to gene discovery.

Original languageEnglish (US)
Pages (from-to)594-597
Number of pages4
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume2
StatePublished - Dec 1 1997
Externally publishedYes
EventProceedings of the 1997 19th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Chicago, IL, USA
Duration: Oct 30 1997Nov 2 1997

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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