A method for linking computed image features to histological semantics in neuropathology

Lessmann B, Nattkemper TW, Hans VH, Degenhard A (2007)
Journal of Biomedical Informatics 40(6): 631-641.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Lessmann, B.; Nattkemper, Tim WilhelmUniBi ; Hans, V. H.; Degenhard, A.
Abstract / Bemerkung
In medical image analysis the image content is often represented by features computed from the pixel matrix in order to support the development of improved clinical diagnosis systems. These features need to be interpreted and understood at a clinical level of understanding Many features are of abstract nature, as for instance features derived from a wavelet transform. The interpretation and analysis of such features are difficult. This lack of coincidence between computed features and their meaning for a user in a given situation is commonly referred to as the semantic gap. In this work, we propose a method for feature analysis and interpretation based oil the simultaneous visualization of feature and image domain. Histopathological images of meningiomas WHO (World Health Organization) grade I are represented by features derived from color transforms and the Discrete Wavelet Transform. The wavelet-based feature space is then visualized and explored using unsupervised machine learning methods. We show how to analyze and select features according to their relevance for the description of clinically relevant characteristics. (C) 2007 Elsevier Inc. All rights reserved.
Stichworte
Self Organizing Map; Discrete Wavelet Transform; feature selection; histopathology; image analysis
Erscheinungsjahr
2007
Zeitschriftentitel
Journal of Biomedical Informatics
Band
40
Ausgabe
6
Seite(n)
631-641
ISSN
1532-0464
Page URI
https://pub.uni-bielefeld.de/record/1630749

Zitieren

Lessmann B, Nattkemper TW, Hans VH, Degenhard A. A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics. 2007;40(6):631-641.
Lessmann, B., Nattkemper, T. W., Hans, V. H., & Degenhard, A. (2007). A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics, 40(6), 631-641. doi:10.1016/j.jbi.2007.06.007
Lessmann, B., Nattkemper, T. W., Hans, V. H., and Degenhard, A. (2007). A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics 40, 631-641.
Lessmann, B., et al., 2007. A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics, 40(6), p 631-641.
B. Lessmann, et al., “A method for linking computed image features to histological semantics in neuropathology”, Journal of Biomedical Informatics, vol. 40, 2007, pp. 631-641.
Lessmann, B., Nattkemper, T.W., Hans, V.H., Degenhard, A.: A method for linking computed image features to histological semantics in neuropathology. Journal of Biomedical Informatics. 40, 631-641 (2007).
Lessmann, B., Nattkemper, Tim Wilhelm, Hans, V. H., and Degenhard, A. “A method for linking computed image features to histological semantics in neuropathology”. Journal of Biomedical Informatics 40.6 (2007): 631-641.

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