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Supervised method for cell counting from bright field focus stacks

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI)
PublisherIEEE
Pages391-394
Number of pages4
ISBN (Print)9781479923502
DOIs
Publication statusPublished - 15 Jun 2016
Publication typeA4 Article in a conference publication
EventIEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING -
Duration: 1 Jan 1900 → …

Publication series

Name
ISSN (Print)1945-7928

Conference

ConferenceIEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING
Period1/01/00 → …

Abstract

We present a novel method for cell counting using bright field focus stacks. Our method is based on the use of supervised learning and out-of-focus appearance of cells. Logistic regression was used for classification with intensity values of 25 focal planes as features. Binary erosion with a large circular structuring element was applied as post-processing step. With this simple method we obtained mean F\-score of 0.87 for cell counting with 12 test images, including images of extremely dense populations. The most important features were obtained from out-of-focus images. Thus, we conclude that using several focal planes provides valuable intensity information for cell counting from bright field microscopy.

Keywords

  • Cells & molecules, Confocal, Fluorescence, Image segmentation, Microscopy - Light

Publication forum classification

Field of science, Statistics Finland