An adaptive multirate algorithm for acquisition of fluorescence microscopy data sets

Thomas E. Merryman, Jelena Kovačević

Research output: Contribution to journalArticlepeer-review


We propose an algorithm for adaptive efficient acquisition of fluorescence microscopy data sets using a multirate (MR) approach. We simulate acquisition as part of a larger system for protein classification based on their subcellular location patterns and, thus, strive to maintain the achieved level of classification accuracy as much as possible. This problem is similar to image compression but unique due to additional restrictions, namely causality; we have access only to the information scanned up to that point. While we do want to acquire fewer samples with as low distortion as possible to achieve compression, our goal is to do so while affecting the overall classification accuracy as little as possible. We achieve this by using an adaptive MR scanning scheme which samples the regions of the image area that hold the most pertinent information. Our results show that we can achieve significant compression which we can then use to aquire faster or to increase space resolution of our data set, all while minimally affecting the classification accuracy of the entire system.

Original languageEnglish (US)
Pages (from-to)1246-1253
Number of pages8
JournalIEEE Transactions on Image Processing
Issue number9
StatePublished - Sep 2005

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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