Study of morphological and textural features for classification of oral squamous cell carcinoma by traditional machine learning techniques.

Journal: Cancer reports (Hoboken, N.J.)
Published Date: Oct 7, 2020

Abstract

BACKGROUND: Oral squamous cell carcinoma (OSCC) is the most prevalent form of oral cancer. Very few researches have been carried out for the automatic diagnosis of OSCC using artificial intelligence techniques. Though biopsy is the ultimate test for cancer diagnosis, analyzing a biopsy report is a very much challenging task. To develop computer-assisted software that will diagnose cancerous cells automatically is very important and also a major need of the hour.

Authors

  • Tabassum Yesmin Rahman
    Department of Computer Science & IT, Cotton University, Panbazar, Guwahati 781001, Assam, India.
  • Lipi B Mahanta
    Central Computational and Numerical Sciences Division, Institute of Advanced Study in Science and Technology, Paschim Boragaon, Guwahati 781035, Assam, India. Electronic address: lbmahanta@iasst.gov.in.
  • Hiten Choudhury
    Department of Computer Science & IT, Cotton University, Guwahati, India.
  • Anup K Das
    Arya Wellness Centre, Bhangagarh, Guwahati 781032, Assam, India.
  • Jagannath D Sarma
    Dr. B Borooah Cancer Institute, Bishnu Rabha Nagar, Guwahati 781016, Assam, India.

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