Detection of oral cancer and oral potentially malignant disorders using artificial intelligence‐based image analysis-Reference-Cited by-同舟云学术

Detection of oral cancer and oral potentially malignant disorders using artificial intelligence‐based image analysis

Published:2024-06-11 Issue:9 Volume:46 Page:2253-2260
ISSN:1043-3074
Container-title:Head & Neck
language:en
Short-container-title:Head & Neck

Author:

Kouketsu Atsumu¹,Doi Chiaki²,Tanaka Hiroaki²,Araki Takashi²,Nakayama Rina²,Toyooka Tsuguyoshi²,Hiyama Satoshi²,Iikubo Masahiro³,Osaka Ken⁴,Sasaki Keiichi⁵,Nagai Hirokazu⁶,Sugiura Tsuyoshi¹,Yamauchi Kensuke⁷,Kuroda Kanako¹⁷,Yanagisawa Yuta¹⁷,Miyashita Hitoshi¹⁸,Kajita Tomonari¹,Iwama Ryosuke¹,Kurobane Tsuyoshi¹,Takahashi Tetsu¹⁷

Affiliation:

1. Division of Oral and Maxillofacial Oncology and Surgical Sciences, Department of Disease Management Dentistry Tohoku University Graduate School of Dentistry Sendai Japan

2. X‐Tech Development Department NTT Docomo Inc. Tokyo Japan

3. Division of Dental Informatics and Radiology Tohoku University Graduate School of Dentistry Sendai Japan

4. Department of International and Community Oral Health Tohoku University Graduate School of Dentistry Sendai Japan

5. Division of Dental and Digital Forensics Tohoku University Graduate School of Dentistry Sendai Japan

6. Department of Oral and Maxillofacial Surgery Sendai City Hospital Sendai Japan

7. Division of Oral and Maxillofacial Reconstructive Surgery, Department of Disease Management Dentistry Tohoku University Graduate School of Dentistry Sendai Japan

8. Department of Oral and Maxillofacial Surgery Tohoku Medical and Pharmaceutical University Hospital Sendai Japan

Abstract

AbstractBackgroundWe aimed to construct an artificial intelligence‐based model for detecting oral cancer and dysplastic leukoplakia using oral cavity images captured with a single‐lens reflex camera.Subjects and methodsWe used 1043 images of lesions from 424 patients with oral squamous cell carcinoma (OSCC), leukoplakia, and other oral mucosal diseases. An object detection model was constructed using a Single Shot Multibox Detector to detect oral diseases and their locations using images. The model was trained using 523 images of oral cancer, and its performance was evaluated using images of oral cancer (n = 66), leukoplakia (n = 49), and other oral diseases (n = 405).ResultsFor the detection of only OSCC versus OSCC and leukoplakia, the model demonstrated a sensitivity of 93.9% versus 83.7%, a negative predictive value of 98.8% versus 94.5%, and a specificity of 81.2% versus 81.2%.ConclusionsOur proposed model is a potential diagnostic tool for oral diseases.

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hed.27843

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