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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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Bibliographische Detailangaben
Hauptverfasser: Wienert, Stephan (VerfasserIn) , Heim, Daniel (VerfasserIn) , Kotani, Manato (VerfasserIn) , Lindequist, Björn (VerfasserIn) , Stenzinger, Albrecht (VerfasserIn) , Ishii, Masaru (VerfasserIn) , Hufnagl, Peter (VerfasserIn) , Beil, Michael (VerfasserIn) , Dietel, Manfred (VerfasserIn) , Denkert, Carsten (VerfasserIn) , Klauschen, Frederick (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 27 February 2013
In: Diagnostic pathology
Year: 2013, Jahrgang: 8, Pages: 1-8
ISSN:1746-1596
DOI:10.1186/1746-1596-8-34
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/1746-1596-8-34
Volltext
Verfasserangaben:Stephan Wienert, Daniel Heim, Manato Kotani, Björn Lindequist, Albrecht Stenzinger, Masaru Ishii, Peter Hufnagl, Michael Beil, Manfred Dietel, Carsten Denkert and Frederick Klauschen
Beschreibung
Zusammenfassung: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.
Beschreibung:Gesehen am 08.11.2021
Beschreibung:Online Resource
ISSN:1746-1596
DOI:10.1186/1746-1596-8-34

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