Artificial intelligence based assessment and application of imaging techniques for early diagnosis in oral cancers

Nadimul Hoda; Aastha Moza; Akshay A. Byadgi; K. S. Sabitha

doi:10.18203/2349-2902.isj20240195

Authors

Nadimul Hoda Department of Oral Oncology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, India
Aastha Moza Department of Oral Oncology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, India
Akshay A. Byadgi Department of Oral Oncology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, India
K. S. Sabitha Department of Oral Oncology, Kidwai Memorial Institute of Oncology, Bengaluru, Karnataka, India

DOI:

https://doi.org/10.18203/2349-2902.isj20240195

Keywords:

AI, CNN, Optical imaging, Deep learning

Abstract

Diagnosis at an early stage is the most crucial and decisive outcome in oral cancers. The main objective of this study was to give a brief summary of various emerging optical imaging artificial intelligence (AI) based techniques with their application and implications for the improvements in oral cancer detection. Early diagnosis of oral cancer helps in facilitating early treatment outcome and to predict overall prognosis of the patient. The review talks about the usage of convolution neural networks (CNN) being used for classification of oral cancer images. Further which morphological operations are used for image assembly segmentation of the cancer regions and then deep learning algorithm is utilized to differentiate the cancer lesion regions into mild or severe lesion regions.

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