Creating a Medical Imaging Workflow Based on FHIR, DICOMweb, and SVG

Autor: Shih-Tsang Tang, Victoria Tjia, Thalia Noga, Jeshika Febri, Chung-Yueh Lien, Woei-Chyn Chu, Chin-Yu Chen, Chia-Hung Hsiao
Rok vydání: 2023
Předmět:
Zdroj: Journal of Digital Imaging.
ISSN: 1618-727X
DOI: 10.1007/s10278-021-00522-6
Popis: This paper proposes a web-based workflow scheme for the organization of medical images using FHIR and DICOM servers equipped with standard RESTful APIs. In our integrated workflow, the client systems (including order placer, scheduler, imaging modality, viewer, and report creator) use standard FHIR and DICOMweb APIs. The proposed scheme also facilitates the creation of reports formatted as standard FHIR resources. This paper leverages W3C Scalable Vector Graphics (SVG) to record the image graphic annotations, and encapsulates the SVG image annotation in FHIR observation. FHIR DiagnosticReports and Observations are used to encapsulate reports, findings, and annotations, thereby facilitating the implementation and integration of the scheme within existing structures. The proposed scheme also provides the potential to make it possible to convert results of Computer Aided Detection/Diagnosis from medical images into FHIR DiagnosticReports and Observations to be stored on a FHIR server. The resulting web-based solution uses FHIR XML and/or JSON data to record and exchange information related to imaging workflow. It can also be used to store imaging reports, findings, and annotations linked to the images using the DICOM WADO-RS protocol. As a result, it is possible to integrate all information that is created in medical imaging workflow. Finally, the proposed scheme is easily integrated with other FHIR systems.
Databáze: OpenAIRE