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- Title
Image collection and annotation platforms to establish a multi‐source database of oral lesions.
- Authors
Rajendran, Senthilmani; Lim, Jian Han; Yogalingam, Kohgulakuhan; Kallarakkal, Thomas George; Zain, Rosnah Binti; Jayasinghe, Ruwan Duminda; Rimal, Jyotsna; Kerr, Alexander Ross; Amtha, Rahmi; Patil, Karthikeya; Welikala, Roshan Alex; Lim, Ying Zhi; Remagnino, Paolo; Gibson, John; Tilakaratne, Wanninayake Mudiyanselage; Liew, Chee Sun; Yang, Yi‐Hsin; Barman, Sarah Ann; Chan, Chee Seng; Cheong, Sok Ching
- Abstract
Objective: To describe the development of a platform for image collection and annotation that resulted in a multi‐sourced international image dataset of oral lesions to facilitate the development of automated lesion classification algorithms. Materials and Methods: We developed a web‐interface, hosted on a web server to collect oral lesions images from international partners. Further, we developed a customised annotation tool, also a web‐interface for systematic annotation of images to build a rich clinically labelled dataset. We evaluated the sensitivities comparing referral decisions through the annotation process with the clinical diagnosis of the lesions. Results: The image repository hosts 2474 images of oral lesions consisting of oral cancer, oral potentially malignant disorders and other oral lesions that were collected through MeMoSA® UPLOAD. Eight‐hundred images were annotated by seven oral medicine specialists on MeMoSA®ANNOTATE, to mark the lesion and to collect clinical labels. The sensitivity in referral decision for all lesions that required a referral for cancer management/surveillance was moderate to high depending on the type of lesion (64.3%–100%). Conclusion: This is the first description of a database with clinically labelled oral lesions. This database could accelerate the improvement of AI algorithms that can promote the early detection of high‐risk oral lesions.
- Subjects
PUBLIC health surveillance; IMAGE storage &; retrieval systems; MEDICAL information storage &; retrieval systems; HEALTH services accessibility; MOUTH tumors; USER interfaces; ORAL diseases; EARLY detection of cancer; AUTOMATION; MEDICAL referrals; DESCRIPTIVE statistics; RESEARCH funding; DECISION making in clinical medicine; ELECTRONIC health records; SENSITIVITY &; specificity (Statistics); ALGORITHMS; WORLD Wide Web; DISEASE management
- Publication
Oral Diseases, 2023, Vol 29, Issue 5, p2230
- ISSN
1354-523X
- Publication type
Article
- DOI
10.1111/odi.14206