A fractal dimension based optimal wavelet packet analysis technique for classification of meningioma brain tumours

Al-Kadi, Omar (2009) A fractal dimension based optimal wavelet packet analysis technique for classification of meningioma brain tumours. 2009 IEEE International Conference on Image Processing, Cairo, Egypt, 07 Nov - 11 Nov 2009. Published in: Proceedings of the 16th IEEE International Conference on Image Processing (ICIP); Cairo, Egypt; 7 Nov - 11 Nov 2009. 4125-4128. Institute of Electrical and Electronics Engineers ISSN 1522-4880 ISBN 9781424456536

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With the heterogeneous nature of tissue texture, using a single resolution approach for optimum classification might not suffice. In contrast, a multiresolution wavelet packet analysis can decompose the input signal into a set of frequency subbands giving the opportunity to characterise the texture at the appropriate frequency channel. An adaptive best bases algorithm for optimal bases selection for meningioma histopathological images is proposed, via applying the fractal dimension (FD) as the bases selection criterion in a tree-structured manner. Thereby, the most significant subband that better identifies texture discontinuities will only be chosen for further decomposition, and its fractal signature would represent the extracted feature vector for classification. The best basis selection using the FD outperformed the energy based selection approaches, achieving an overall classification accuracy of 91.25% as compared to 83.44% and 73.75% for the co-occurrence matrix and energy texture signatures; respectively.

Item Type: Conference Proceedings
Additional Information: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Texture analysis, multiresolution representation, wavelet packet, fractal dimension, Bayesian classification
Schools and Departments: School of Engineering and Informatics > Informatics
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Depositing User: Omar Al-Kadi
Date Deposited: 15 May 2012 11:03
Last Modified: 20 Mar 2018 14:57
URI: http://sro.sussex.ac.uk/id/eprint/37861

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