Hyperspectral imaging with wavelet transform for classification of colon tissue biopsy samples

Khalid Masood

doi:10.1117/12.797667

15 September 2008 Hyperspectral imaging with wavelet transform for classification of colon tissue biopsy samples

Khalid Masood

Proceedings Volume 7073, Applications of Digital Image Processing XXXI; 707319 (2008) https://doi.org/10.1117/12.797667
Event: Optical Engineering + Applications, 2008, San Diego, California, United States

Abstract

Automatic classification of medical images is a part of our computerised medical imaging programme to support the pathologists in their diagnosis. Hyperspectral data has found its applications in medical imagery. Its usage is increasing significantly in biopsy analysis of medical images. In this paper, we present a histopathological analysis for the classification of colon biopsy samples into benign and malignant classes. The proposed study is based on comparison between 3D spectral/spatial analysis and 2D spatial analysis. Wavelet textural features in the wavelet domain are used in both these approaches for classification of colon biopsy samples. Experimental results indicate that the incorporation of wavelet textural features using a support vector machine, in 2D spatial analysis, achieve best classification accuracy.

Citation Download Citation

Khalid Masood "Hyperspectral imaging with wavelet transform for classification of colon tissue biopsy samples", Proc. SPIE 7073, Applications of Digital Image Processing XXXI, 707319 (15 September 2008); https://doi.org/10.1117/12.797667

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