TY - JOUR AU - Tahir, Muhammad Atif AU - Bouridane, Ahmed AU - Kurugollu, Fatih AU - Amira, Abbes PY - 2005 DA - 2005/08/25 TI - A Novel Prostate Cancer Classification Technique Using Intermediate Memory Tabu Search JO - EURASIP Journal on Advances in Signal Processing SP - 906054 VL - 2005 IS - 14 AB - 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. SN - 1687-6180 UR - https://doi.org/10.1155/ASP.2005.2241 DO - 10.1155/ASP.2005.2241 ID - Tahir2005 ER -