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JBI
2007

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

9 years 11 months ago
A method for linking computed image features to histological semantics in neuropathology
In medical image analysis, the image content is often represented by computed features that need to be interpreted at a clinical level of understanding to support lopment of clinical diagnosis systems. Many features are of abstract nature, as for instance features derived from a wavelet transform. The interpretation and analysis of such features is 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 on the simultaneous visualization of feature and image domain. Histopathological images of meningioma WHO (World Health Organization) grade I are firstly color transformed and then characterized by features derived from the Discrete Wavelet Transform. The wavelet-based feature space is then visualized and explored using unsupervised machine learning methods. Our approach allows to analyze and select feature...
Birgit Lessmann, Tim W. Nattkemper, V. H. Hans, An
Added 15 Dec 2010
Updated 15 Dec 2010
Type Journal
Year 2007
Where JBI
Authors Birgit Lessmann, Tim W. Nattkemper, V. H. Hans, Andreas Degenhard
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