Towards an image analysis toolbox for high-throughput Drosophila embryo RNAi screens

Ryan A. Kellogg, Amina Chebira, Anupam Goyal, Philip A. Cuadra, Stefan F. Zappe, Jonathan S. Minden, Jelena Kovačević

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

Abstract

We build an image analysis toolbox for high-throughput Drosophila embryo RNAi screens. The goal is to tag the embryo as normal, developmentally delayed or abnormal based on the ventral furrow formation. We break the problem into two parts: in the first, we detect the developmental stage based on the progress of the ventral furrow formation, and in the second, we tag the embryo as normal/developmentally delayed/abnormal based on the stage detected and the elapsed time. The crux of the algorithm is the multiresolution classifier, and we show that, by classifying in multiresolution spaces, we obtain better results than by classifying the embryo image alone. The final 2D accuracy obtained was 93.17%, while by using 3D information, it increased to 98.35%.

Original languageEnglish (US)
Title of host publication2007 4th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro - Proceedings
Pages288-291
Number of pages4
DOIs
StatePublished - 2007
Event2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07 - Arlington, VA, United States
Duration: Apr 12 2007Apr 15 2007

Publication series

Name2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro - Proceedings

Other

Other2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro; ISBI'07
Country/TerritoryUnited States
CityArlington, VA
Period4/12/074/15/07

Keywords

  • Classification
  • Drosophila
  • High-throughput
  • Multiresolution
  • Screening

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • General Medicine

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