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...
Gespeichert in:
| Hauptverfasser: | , , , , , , , , , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
27 February 2013
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| 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 |
| Verfasserangaben: | 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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| 520 | |a 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. | ||
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