Open Access Software

CognitionMaster: an object-based image analysis framework

Stephan Wienert12, Daniel Heim2, Manato Kotani34, Björn Lindequist5, Albrecht Stenzinger6, Masaru Ishii34, Peter Hufnagl15, Michael Beil7, Manfred Dietel1, Carsten Denkert1 and Frederick Klauschen1*

Author affiliations

1 Institute of Pathology, Charité University Hospital Berlin, Charitéplatz 1, Berlin, 10117, Germany

2 VMscope GmbH, Charitéplatz 1, Berlin, 10117, Germany

3 Laboratory of Cellular Dynamics, WPI-IFReC, Osaka University, 3-1 Yamada-oka, Suita, Osaka, 5650871, Japan

4 CREST, Japan Science and Technology Agency (JST), 5 Sanbancho, Chiyoda-ku, Tokyo, 1020075, Japan

5 University of Applied Sciences Berlin, Wilhelminenhofstraße 75A, Berlin, 12459, Germany

6 Institute of Pathology, University Hospital Heidelberg, Im Neuenheimer Feld 220/221, Heidelberg, 69120, Germany

7 Department of Medicine I, University of Ulm, Albert-Einstein-Allee 23, Ulm, 89081, Germany

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Citation and License

Diagnostic Pathology 2013, 8:34  doi:10.1186/1746-1596-8-34

Published: 27 February 2013

Abstract

Background

Automated image analysis methods are becoming more and more important to extract and quantify image features in microscopy-based biomedical studies and several commercial or open-source tools are available. However, most of the approaches rely on pixel-wise operations, a concept that has limitations when high-level object features and relationships between objects are studied and if user-interactivity on the object-level is desired.

Results

In this paper we present an open-source software that facilitates the analysis of content features and object relationships by using objects as basic processing unit instead of individual pixels. Our approach enables also users without programming knowledge to compose “analysis pipelines“ that exploit the object-level approach. We demonstrate the design and use of example pipelines for the immunohistochemistry-based cell proliferation quantification in breast cancer and two-photon fluorescence microscopy data about bone-osteoclast interaction, which underline the advantages of the object-based concept.

Conclusions

We introduce an open source software system that offers object-based image analysis. The object-based concept allows for a straight-forward development of object-related interactive or fully automated image analysis solutions. The presented software may therefore serve as a basis for various applications in the field of digital image analysis.

Keywords:
Software; Open source; Image analysis; Object-based image analysis