External-attention-based deep neural network model for reliable detection of oral cancer from histopathological images

Bhaswati Singha Deo; Mayukha Pal; Asima Pradhan

doi:10.1117/12.2669798

11 May 2023 External-attention-based deep neural network model for reliable detection of oral cancer from histopathological images

Bhaswati Singha Deo, Mayukha Pal, Asima Pradhan

Author Affiliations +

Proceedings Volume 12638, Women in Optics and Photonics in India 2022; 1263808 (2023) https://doi.org/10.1117/12.2669798
Event: Women in Optics and Photonics in India, 2022, Bangalore, India

Conference Poster

Abstract

Oral cancer is one of the deadliest diseases around the world with varied morphological traits, hence making it difficult to manually achieve accurate classification. Further, the traditional methods of diagnosis used by clinicians can be time-consuming and prone to error. Therefore, computer-assisted histopathological image classification is of extreme importance for the detection of oral cancer. We propose an image classification model known as External Attention Transformer model based on external attention mechanism, aiming to extract discriminating fine features from oral cancer tissue sections and their normal counterparts. We have used 4946 oral histopathological images classified into two categories: normal and oral squamous cell carcinoma (OSCC). Of the total images, 2435 of them are categorized as normal and 2511 as OSCC. External attention based deep neural network model attained 96.97% classification accuracy. Sensitivity and specificity were recorded as 97.61% and 96.41% respectively. It is found that the effectiveness of artificial intelligence methods for classifying oral cancer has significantly improved in comparison to leading edge methods, and this has a potential for early oral cancer detection.

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Bhaswati Singha Deo, Mayukha Pal, and Asima Pradhan "External-attention-based deep neural network model for reliable detection of oral cancer from histopathological images", Proc. SPIE 12638, Women in Optics and Photonics in India 2022, 1263808 (11 May 2023); https://doi.org/10.1117/12.2669798

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