Graphics and Imaging Laboratory (GILAB), Universitat de Girona, Edifici P-IV, 17001 Girona, Catalonia, Spain.
Int J Med Inform. 2020 May;137:104098. doi: 10.1016/j.ijmedinf.2020.104098. Epub 2020 Feb 11.
The aim of the paper is twofold. First, we present Starviewer, a DICOM viewer developed in C++ with a core component built on top of open-source libraries. The viewer supports extensions that implement functionalities and front-ends for specific use cases. Second, we propose an adaptable evaluation framework based on a set of criteria weighted according to user needs. The framework can consider different user profiles and allow criteria to be decomposed in subcriteria and grouped in more general categories making a multi-level hierarchical structure that can be analysed at different levels of detail to make scores interpretation more comprehensible.
Different examples to illustrate Starviewer functionalities and its extensions are presented. In addition, the proposed evaluation framework is used to compare Starviewer with four open-source viewers regarding their functionalities for daily clinical practice. In a range from 0 to 10, the final scores are: Horos (7.7), Starviewer (6.2), Weasis (6.0), Ginkgo CADx (4.1), and medInria (3.8).
Starviewer provides basic and advanced features for daily image diagnosis needs as well as a modular design that enables the development of custom extensions. The evaluation framework is useful to understand and prioritize new development goals, and can be easily adapted to express different needs by altering the weights. Moreover, it can be used as a complement to maturity models.
本文的目的有两个。首先，我们展示了 Starviewer，这是一个用 C++开发的 DICOM 查看器，其核心组件建立在开源库之上。该查看器支持实现特定用例功能和前端的扩展。其次，我们提出了一个基于根据用户需求加权的一组标准的可适应评估框架。该框架可以考虑不同的用户配置文件，并允许将标准分解为子标准，并将其分组到更一般的类别中，从而形成一个多层次的层次结构，可以在不同的详细级别进行分析，以便更易于理解得分解释。
展示了不同的示例来说明 Starviewer 的功能及其扩展。此外，还使用所提出的评估框架将 Starviewer 与四个开源查看器进行比较，以评估它们在日常临床实践中的功能。分数范围从 0 到 10，最终分数为：Horos（7.7），Starviewer（6.2），Weasis（6.0），Ginkgo CADx（4.1）和 medInria（3.8）。
Starviewer 提供了基本和高级功能，以满足日常图像诊断需求，以及模块化设计，可实现自定义扩展的开发。评估框架有助于理解和确定新的开发目标优先级，并且可以通过更改权重轻松适用于表达不同的需求。此外，它可以用作成熟度模型的补充。
