Visual Exploration of Pathology Images by a Discrete Wavelet Transform Preprocessed Locally Linear Embedding

The information content of large collections of histopathological images can be explored utilizing computer-based techniques that can help the user to explore the similarity between different brain tumor types. To visually inspect the degree of similarity between different tumors, we propose a combined approach based on the Discrete Wavelet Transform (DWT) and Locally Linear Embedding (LLE). The former is employed as a preprocessing utility, the latter achieves the dimensional reduction required for visualization.

Authors and Affiliations

1. Theoretical Physics, University of Bielefeld, Bielefeld, Germany

   Claudio Varini, Birgit Lessmann & Andreas Degenhard

2. Applied Neuroinformatics Group, University of Bielefeld, Bielefeld, Germany

   Claudio Varini, Birgit Lessmann & Tim Nattkemper

3. Institute of Neuropathology, Evangelischesn Krankenhaus, Bielefeld, Germany

   Volkmar Hans

Editors and Affiliations

1. Institut für Medizinische Informatik, Universitätsklinikum Hamburg-Eppendorf, Martinistraße 52, 20246, Hamburg

   Heinz Handels  & Jan Ehrhardt  & 

2. Institut für Medizinische Statistik und Epidemiologie, Technische Universität München, Klinikum rechts der Isar, Ismaninger Straße 22, 81675, München

   Alexander Horsch

3. Abteilung für Medizinische und Biologische Informatik / H0100, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120, Heidelberg

   Hans-Peter Meinzer

4. Institut für Medizinische Informatik, Biometrie und Epidemiologie Campus Benjamin Franklin, Charité — Universitätsmedizin Berlin, Hindenburgdamm 30, 12000, Berlin

   Thomas Tolxdorff

Reprints and permissions

© 2006 Springer-Verlag Berlin Heidelberg

Policies and ethics