• Users Online: 4249
  • Print this page
  • Email this page
ORIGINAL ARTICLE
Year : 2022  |  Volume : 12  |  Issue : 4  |  Page : 278-284

A Novel Texture Extraction-Based Compressive Sensing for Lung Cancer Classification


1 School of Applied Science, Telkom University, Bandung, Jawa Barat, Indonesia
2 School of Electrical Engineering, Telkom University, Bandung, Jawa Barat, Indonesia
3 Department of Communication Technology and Networking, Faculty of Computer Science and Information Technology, University Putra Malaysia, Seri Kembangan, Malaysia

Correspondence Address:
Indrarini Dyah Irawati
School of Applied Science, Telkom University, Bandung, Jawa Barat
Indonesia
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmss.jmss_127_21

Rights and Permissions

Background: Lung cancer images require large memory storage and transmission bandwidth for sending the data. Compressive sensing (CS), as a method with a statistical approach in signal sampling, provides different output patterns based on information sources. Thus, it can be considered that CS can be used for feature extraction of compressed information. Methods: In this study, we proposed a novel texture extraction-based CS for lung cancer classification. We classify three types of lung cancer, including adenocarcinoma (ACA), squamous cell carcinoma (SCC), and benign lung cancer (N). The classification is carried out based on texture extraction, which is processed in 2 stages, the first stage to detect N and the second to detect ACA and SCC. Results: The simulation results show that two-stage texture extraction can improve accuracy by an average of 84%. The proposed system is expected to be decision support in assisting clinical diagnosis. In terms of technical storage, this system can save memory resources. Conclusions: The proposed two-step texture extraction system combined with CS and K- Nearest Neighbor has succeeded in classifying lung cancer with high accuracy; the system can also save memory storage. It is necessary to examine the complexity of the proposed method so that it can be analyzed further.


[FULL TEXT] [PDF]*
Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed479    
    Printed14    
    Emailed0    
    PDF Downloaded49    
    Comments [Add]    

Recommend this journal