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Image collection and annotation platforms to establish a multi-source database of oral lesions.
- Source :
-
Oral diseases [Oral Dis] 2023 Jul; Vol. 29 (5), pp. 2230-2238. Date of Electronic Publication: 2022 Apr 25. - Publication Year :
- 2023
-
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.<br />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.<br />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 <superscript>®</superscript> UPLOAD. Eight-hundred images were annotated by seven oral medicine specialists on MeMoSA <superscript>®</superscript> 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%).<br />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.<br /> (© 2022 Wiley Periodicals LLC.)
- Subjects :
- Humans
Algorithms
Mouth Neoplasms
Subjects
Details
- Language :
- English
- ISSN :
- 1601-0825
- Volume :
- 29
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Oral diseases
- Publication Type :
- Academic Journal
- Accession number :
- 35398971
- Full Text :
- https://doi.org/10.1111/odi.14206