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Automatic adaptation of filter sequences for cell counting

Uroš Čibej and Jasna Lojk and Mojca Pavlin and Luka Šajn Automatic adaptation of filter sequences for cell counting. MIPRO 2015: proceedings / 38th International Convention, May 25-29, 2015, Opatija, Croatia ; edited by Petar Biljanović ; organized by MIPRO Croatian Society .

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    Manual cell counting in microscopic images is usually tedious, time consuming and prone to human error. Several programs for automatic cell counting have been developed so far, but most of them demand some specific knowledge of image analysis and/or manual fine tuning of various parameters. Even if a set of filters is found and fine tuned to the specific application, small changes to the image attributes might make the automatic counter very unreliable. The goal of this article is to present a new application that overcomes this problem by learning the set of parameters for each application, thus making it more robust to changes in the input images. The users must provide only a small representative subset of images and their manual count, and the program offers a set of automatic counters learned from the given input. The user can check the counters and choose the most suitable one. The resulting application (which we call Learn123) is specifically tailored to the practitioners, i.e. even though the typical workflow is more complex, the application is easy to use for non-technical experts.

    Item Type: Article
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Divisions: Faculty of Computer and Information Science > Computer Vision Laboratory
    Item ID: 3087
    Date Deposited: 14 Sep 2015 13:49
    Last Modified: 14 Sep 2015 13:49
    URI: http://eprints.fri.uni-lj.si/id/eprint/3087

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