Image collection and annotation platforms to establish a multi‐source database of oral lesions.
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, host...
| Publicado en: | Oral Diseases Vol. 29; no. 5; pp. 2230 - 2239 |
|---|---|
| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jul2023
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=164230648&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 164230648 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 1354523X DZP jtl: Oral Diseases issn: 1354523X maglogo: Y pubinfo: dt: Jul2023 vid: 29 iid: 5 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 164230648 156487203 164230648 164230648 10.1111/odi.14206 164230648 ppf: 2230 ppct: 9 formats: tig: atl: Image collection and annotation platforms to establish a multi‐source database of oral lesions. aug: au: 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 affil: Digital Health Research Unit, Cancer Research Malaysia, Subang Jaya, Malaysia sug: subj: Image Retrieval Systems Mouth Diseases Classification Automation Algorithms Human User-Computer Interface World Wide Web Referral and Consultation Decision Making, Clinical Clinical Data Repository Sensitivity and Specificity Disease Management Disease Surveillance Descriptive Statistics Health Services Accessibility Funding Source Mouth Neoplasms Diagnosis Early Detection of Cancer ab: 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. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|