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CognitionMaster: an object-based image analysis framework

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...

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Bibliographic Details
Main Authors: Wienert, Stephan (Author) , Heim, Daniel (Author) , Kotani, Manato (Author) , Lindequist, Björn (Author) , Stenzinger, Albrecht (Author) , Ishii, Masaru (Author) , Hufnagl, Peter (Author) , Beil, Michael (Author) , Dietel, Manfred (Author) , Denkert, Carsten (Author) , Klauschen, Frederick (Author)
Format: Article (Journal)
Language:English
Published: 27 February 2013
In: Diagnostic pathology
Year: 2013, Volume: 8, Pages: 1-8
ISSN:1746-1596
DOI:10.1186/1746-1596-8-34
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/1746-1596-8-34
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Author Notes:Stephan Wienert, Daniel Heim, Manato Kotani, Björn Lindequist, Albrecht Stenzinger, Masaru Ishii, Peter Hufnagl, Michael Beil, Manfred Dietel, Carsten Denkert and Frederick Klauschen
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Summary: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.
Item Description:Gesehen am 08.11.2021
Physical Description:Online Resource
ISSN:1746-1596
DOI:10.1186/1746-1596-8-34

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