Asian Science Citation Index is committed to provide an authoritative, trusted and significant information by the coverage of the most important and influential journals to meet the needs of the global scientific community.  
ASCI Database
308-Lasani Town,
Sargodha Road,
Faisalabad, Pakistan
Fax: +92-41-8815544
Contact Via Web
Suggest a Journal
Information Technology Journal
Year: 2014  |  Volume: 13  |  Issue: 10  |  Page No.: 1716 - 1722

Computerized Distinction of Improved Fuzzy Support Machine for Imageology Character of Benign and Malighant Pulmonary Nodules

Yan Qiang, Bo Pei, Wei Wei, Jianfeng Yang and Juanjuan Zhao    

Abstract: In order to improve the accuracy of the solitary pulmonary nodule diagnosis with medical signs in medical imaging diagnostics, a novel computer-aided classification method is developed. In the view of the existing problems in the lung cancer diagnosis such as the large number of data and the low diagnose efficiency. In order to solve the problem, a new classification method based on the Fuzzy Support Vector Machine (FSVM) was developed to choose the lung with suspicious lesion at an early stage. In this method, the membership function was improved based on the spectral clustering theory which ensures each sample has two membership degrees that guarantees the class of the specific sample more reasonably. The proposed method was used to classify benign and malignant of the pulmonary nodules, the parameters show this method can distinguish the noise and outliers samples more effectively, compared with the traditional fuzzy support vector machine method. Thus, the results illustrated the robust to noise capability and the effective classification ability of this method.

Cited References   |    Fulltext    |   Related Articles   |   Back
   
 
 
 
  Related Articles

 
 
 
 
 
 
 
 
 
Copyright   |   Desclaimer   |    Privacy Policy   |   Browsers   |   Accessibility