Susceptibility of Texture Measures to Noise: An Application to Lung Tumor CT Images

Al-Kadi, Omar.S. and Watson, D (2008) Susceptibility of Texture Measures to Noise: An Application to Lung Tumor CT Images. In: 8th IEEE International Conference on BioInformatics and BioEngineering, 8-10 Oct 2008, Athens, Greece.

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Abstract

Five different texture methods are used to investigate their susceptibility to subtle noise occurring in lung tumor Computed Tomography (CT) images caused by acquisition and reconstruction deficiencies. Noise of Gaussian and Rayleigh distributions with varying mean and variance was encountered in the analyzed CT images. Fisher and Bhattacharyya distance measures were used to differentiate between an original extracted lung tumor region of interest (ROI) with a filtered and noisy reconstructed versions. Through examining the texture characteristics of the lung tumor areas by five different texture measures, it was determined that the autocovariance measure was least affected and the gray level co-occurrence matrix was the most affected by noise. Depending on the selected ROI size, it was concluded that the number of extracted features from each texture measure increases susceptibility to noise.

Item Type: Conference or Workshop Item (Paper)
Keywords: Texture analysis,medical noise, CT images, lung tumors
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Q Science > QA Mathematics > QA0076 Computer software
Depositing User: Omar Al-Kadi
Date Deposited: 05 Nov 2008
Last Modified: 30 Nov 2012 16:53
URI: http://sro.sussex.ac.uk/id/eprint/2084
Google Scholar:4 Citations

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