Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks

Kondylakis, Haridimos ; Ciarrocchi, Esther ; Cerda-Alberich, Leonor ; Chouvarda, Ioanna ; Fromont, Lauren A. ; Garcia-Aznar, Jose Manuel (Universidad de Zaragoza) ; Kalokyri, Varvara ; Kosvyra, Alexandra ; Walker, Dawn ; Yang, Guang ; Neri, Emanuele

Resumen: A huge amount of imaging data is becoming available worldwide and an incredible range of possible improvements can be provided by artificial intelligence algorithms in clinical care for diagnosis and decision support. In this context, it has become essential to properly manage and handle these medical images and to define which metadata have to be considered, in order for the images to provide their full potential. Metadata are additional data associated with the images, which provide a complete description of the image acquisition, curation, analysis, and of the relevant clinical variables associated with the images. Currently, several data models are available to describe one or more subcategories of metadata, but a unique, common, and standard data model capable of fully representing the heterogeneity of medical metadata has not been yet developed. This paper reports the state of the art on metadata models for medical imaging, the current limitations and further developments, and describes the strategy adopted by the Horizon 2020 “AI for Health Imaging” projects, which are all dedicated to the creation of imaging biobanks.

Idioma: Inglés

DOI: 10.1186/s41747-022-00281-1

Año: 2022

Publicado en: European radiology experimental 6 (2022), 29 [15 pp.]
ISSN: 2509-9280

Factor impacto CITESCORE: 6.2 - Medicine (Q1)

Factor impacto SCIMAGO: 0.789 - Radiology, Nuclear Medicine and Imaging (Q2)

Financiación: info:eu-repo/grantAgreement/EC/H2020/826494/EU/PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers/PRIMAGE
Financiación: info:eu-repo/grantAgreement/EC/H2020/952103/EU/Novel pan-European imaging platform for artificial intelligence advances in oncology/EuCanImage
Financiación: info:eu-repo/grantAgreement/EC/H2020/952159/EU/An AI Platform integrating imaging data and models, supporting precision care through prostate cancer’s continuum/ ProCAncer-I
Financiación: info:eu-repo/grantAgreement/EC/H2020/952172/EU/Accelerating the lab to market transition of AI tools for cancer management/CHAIMELEON
Financiación: info:eu-repo/grantAgreement/EC/H2020/952179/EU/A multimodal AI-based toolbox and an interoperable health imaging repository for the empowerment of imaging analysis related to the diagnosis, prediction and follow-up of cancer/INCISIVE

Tipo y forma: Article (Published version)

Área (Departamento): Área Mec.Med.Cont. y Teor.Est. (Dpto. Ingeniería Mecánica)