Computer-Aided Diagnosis of Coal Workers’ Pneumoconiosis in Chest X-ray Radiographs Using Machine Learning: A Systematic Literature Review

DOI Web Site 被引用文献1件
  • Liton Devnath
    School of Information and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia
  • Peter Summons
    School of Information and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia
  • Suhuai Luo
    School of Information and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia
  • Dadong Wang
    Quantitative Imaging, CSIRO Data61, Marsfield, Sydney, NSW 2122, Australia
  • Kamran Shaukat
    School of Information and Physical Sciences, The University of Newcastle, Newcastle, NSW 2308, Australia
  • Ibrahim A. Hameed
    Department of ICT and Natural Sciences, Norwegian University of Science and Technology, 7491 Trondheim, Norway
  • Hanan Aljuaid
    Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University (PNU), P.O. Box 84428, Riyadh 11671, Saudi Arabia

説明

<jats:p>Computer-aided diagnostic (CAD) systems can assist radiologists in detecting coal workers’ pneumoconiosis (CWP) in their chest X-rays. Early diagnosis of the CWP can significantly improve workers’ survival rate. The development of the CAD systems will reduce risk in the workplace and improve the quality of chest screening for CWP diseases. This systematic literature review (SLR) amis to categorise and summarise the feature extraction and detection approaches of computer-based analysis in CWP using chest X-ray radiographs (CXR). We conducted the SLR method through 11 databases that focus on science, engineering, medicine, health, and clinical studies. The proposed SLR identified and compared 40 articles from the last 5 decades, covering three main categories of computer-based CWP detection: classical handcrafted features-based image analysis, traditional machine learning, and deep learning-based methods. Limitations of this review and future improvement of the review are also discussed.</jats:p>

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