Visual Exploration of Pathology Images by a Discrete Wavelet Transform Preprocessed Locally Linear Embedding
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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.
[1] Stéphane Mallat,et al. Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..
[2] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .
[3] S T Roweis,et al. Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.
[4] Richard Bellman,et al. Adaptive Control Processes: A Guided Tour , 1961, The Mathematical Gazette.