Tahir, MA, Bouridane, A, Kurugollu, F and Amira, A (2005) A novel prostate cancer classification technique using intermediate memory tabu search. EURASIP JOURNAL ON APPLIED SIGNAL PROCESSING, 2005 (14). pp. 2241-2249. [Journal article]
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The introduction of multispectral imaging in pathology problems such as the identification of prostatic cancer is recent. Unlike conventional RGB color space, it allows the acquisition of a large number of spectral bands within the visible spectrum. This results in a feature vector of size greater than 100. For such a high dimensionality, pattern recognition techniques suffer from the well-known curse of dimensionality problem. The two well-known techniques to solve this problem are feature extraction and feature selection. In this paper, a novel feature selection technique using tabu search with an intermediate-term memory is proposed. The cost of a feature subset is measured by leave-one-out correct-classification rate of a nearest-neighbor (1-NN) classifier. The experiments have been carried out on the prostate cancer textured multispectral images and the results have been compared with a reported classical feature extraction technique. The results have indicated a significant boost in the performance both in terms of minimizing features and maximizing classification accuracy.
|Item Type:||Journal article|
|Keywords:||feature selection; dimensionality reduction; tabu search; 1-NN classifier; prostate cancer classification|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Engineering
|Research Institutes and Groups:||Engineering Research Institute|
Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
|Deposited By:||Dr Abbes Amira|
|Deposited On:||20 May 2010 11:33|
|Last Modified:||25 Jul 2011 12:28|
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