Breast Tumor Detection Algorithm Based on Feature Selection ELM

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Journal of Northeastern University ›› 2013, Vol. 34 ›› Issue (6): 792-796.DOI: -

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Breast Tumor Detection Algorithm Based on Feature Selection ELM

WANG Zhiqiong^1,2， KANG Yan¹， YU Ge²， ZHAO Yingjie³

1. SinoDutch Biomedical and Information Engineering School， Northeastern University， Shenyang 110819， China; 2. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China; 3. Medical imaging Department， Tumor Hospital of Liaoning Province， Shenyang 110042， China.

Received:2012-12-01 Revised:2012-12-01 Online:2013-06-15 Published:2013-12-31
Contact: KANG Yan
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Abstract

Abstract: Breast tumor detection is an effective way for preventing breast cancer， and the classification algorithm of extreme learning machine(ELM) that based on XRay image feature model of breast had been used in computer aided detection of breast tumor. Due to the low learning efficiency and detection accuracy of ELM caused by the dependence between features， a breast tumor detction algorithm was proposed in this paper based on features selection ELM. The methods of impact value selection， sequential forward selection and genetic algorithm were used to improve the performance of ELM. The 490 XRay images used in the experiment came from Tumor Hospital of Liaoning Province， and the results showed that the precision of breast tumor detection could be improved with the proposed method especially for genetic selection algorithm.

Key words: extreme learning machine, genetic selection, impact value selection, sequential forward selection

CLC Number:

TP305

WANG Zhiqiong， KANG Yan， YU Ge， ZHAO Yingjie. Breast Tumor Detection Algorithm Based on Feature Selection ELM[J]. Journal of Northeastern University, 2013, 34(6): 792-796.

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Breast Tumor Detection Algorithm Based on Feature Selection ELM

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