Enhanced swin transformer based tuberculosis classification with segmentation using chest X-ray.

Journal: Journal of X-ray science and technology
PMID: 39973770

Abstract

BACKGROUND:: Tuberculosis disease is the disease that causes significant morbidity and mortality worldwide. Thus, early detection of the disease is crucial for proper treatment and controlling the spread of Tuberculosis disease. Chest X-ray imaging is one of the most widely used diagnostic tools for detecting the Tuberculosis, which is time-consuming, and prone to errors. Nowadays, deep learning model provides the automated classification of medical images with promising outcome.

Authors

  • P Visu
    Department of Artificial Intelligence and Data Science, Velammal Engineering College, Chennai, India.
  • V Sathiya
    Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, India.
  • P Ajitha
    Department of Conservative Dentistry and Endodontics, Saveetha Institute of Medical and Technical Sciences, Saveetha Dental College, Chennai, Tamil Nadu, India.
  • R Surendran
    Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, India.

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