Dicoogle Open Source: The Establishment of a New Paradigm in Medical Imaging

Abstract

The rapid and continuous growth of data volume and its heterogeneity has become one of the most noticeable trends in healthcare, namely in medical imaging. This evolution led to the deployment of specialized information systems supported by the DICOM standard that enables the interoperability of distinct components, including imaging modalities, repositories, and visualization workstations. However, the complexity of these ecosystems leads to challenging learning curves and makes it time-consuming to mock and apply new ideas. Dicoogle is an extensible medical imaging archive server that emerges as a tool to overcome those challenges. Its extensible architecture allows the fast development of new advanced features or extends existent ones. It is currently a fundamental enabling technology in collaborative and telehealthcare environments, including research projects, screening programs, and teleradiology services. The framework is supported by a Learning Pack that includes a description of the web programmatic interface, a software development kit, documentation, and implementation samples. This article gives an in-depth view of the Dicoogle ecosystem, state-of-the-art contributions, and community impact. It starts by presenting an overview of its architectural concept, highlights some of the most representative research backed up by Dicoogle, some remarks obtained from its use in teaching, and worldwide usage statistics of the software. Finally, the positioning of Dicoogle in the medical imaging software field is discussed through comparison with other well-known solutions.

Keywords: DICOM; Dicoogle; Medical imaging; PACS; Teaching; Telehealth-care.

Fig. 1

Dicoogle Architecture

Fig. 2

Architecture of the routing mechanism of incoming objects to Dicoogle

Fig. 3

Screenshot of the WebML web application

Fig. 4

Reported interests by 9041 users that have downloaded Dicoogle since 2018 (data acquired from the download form on the Dicoogle website)

Fig. 5

Downloads per month from the beginning of 2018 until December 2021

Fig. 6

Distribution of students per course from the academic year 2018/2019 until 2020/2021