BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images

Bioinformatics, vol. 36, pp. 4668–4670

Abstract

MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution images. In addition, expert knowledge is needed to adjust parameters. RESULTS: In combination with our image labeling tool, BeadNet enables biologists to easily annotate and process their data reducing the expertise required in many existing image analysis pipelines. BeadNet outperforms state-of-the-art-algorithms in terms of missing, added and total amount of beads. AVAILABILITY AND IMPLEMENTATION: BeadNet (software, code and dataset) is available at https://bitbucket.org/t_scherr/beadnet. The image labeling tool is available at https://bitbucket.org/abartschat/imagelabelingtool. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors 8

1. Tim Scherr corresponding
   Affiliation as printed

   Institute for Automation and Applied Informatics , Eggenstein-Leopoldshafen 76344, Germany

2. Karolin Streule

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute of Biological and Chemical Systems – Functional Molecular Systems, Karlsruhe Institute of Technology , Eggenstein-Leopoldshafen 76344, Germany

3. Andreas Bartschat
   Affiliation as printed

   Institute for Automation and Applied Informatics , Eggenstein-Leopoldshafen 76344, Germany

4. Moritz Böhland
   Affiliation as printed

   Institute for Automation and Applied Informatics , Eggenstein-Leopoldshafen 76344, Germany

5. Johannes Stegmaier Aachen Institute of Imaging & Computer Vision

   RWTH Aachen University

   Affiliation as printed

   Institute of Imaging and Computer Vision, RWTH Aachen University , Aachen 52074, Germany

6. Markus Reischl
   Affiliation as printed

   Institute for Automation and Applied Informatics , Eggenstein-Leopoldshafen 76344, Germany

7. Véronique Orian‐Rousseau

   Karlsruhe Institute of Technology

   Affiliation as printed

   Institute of Biological and Chemical Systems – Functional Molecular Systems, Karlsruhe Institute of Technology , Eggenstein-Leopoldshafen 76344, Germany

8. Ralf Mikut corresponding
   Affiliation as printed

   Institute for Automation and Applied Informatics , Eggenstein-Leopoldshafen 76344, Germany