School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024, China.
Faculty of Information Technology, University of Jyväskylä, 40100, Jyväskylä, Finland.
J Digit Imaging. 2022 Dec;35(6):1623-1633. doi: 10.1007/s10278-022-00660-5. Epub 2022 Jun 29.
The development of medical image analysis algorithm is a complex process including the multiple sub-steps of model training, data visualization, human-computer interaction and graphical user interface (GUI) construction. To accelerate the development process, algorithm developers need a software tool to assist with all the sub-steps so that they can focus on the core function implementation. Especially, for the development of deep learning (DL) algorithms, a software tool supporting training data annotation and GUI construction is highly desired. In this work, we constructed AnatomySketch, an extensible open-source software platform with a friendly GUI and a flexible plugin interface for integrating user-developed algorithm modules. Through the plugin interface, algorithm developers can quickly create a GUI-based software prototype for clinical validation. AnatomySketch supports image annotation using the stylus and multi-touch screen. It also provides efficient tools to facilitate the collaboration between human experts and artificial intelligent (AI) algorithms. We demonstrate four exemplar applications including customized MRI image diagnosis, interactive lung lobe segmentation, human-AI collaborated spine disc segmentation and Annotation-by-iterative-Deep-Learning (AID) for DL model training. Using AnatomySketch, the gap between laboratory prototyping and clinical testing is bridged and the development of MIA algorithms is accelerated. The software is opened at https://github.com/DlutMedimgGroup/AnatomySketch-Software .
医学图像分析算法的开发是一个复杂的过程，包括模型训练、数据可视化、人机交互和图形用户界面 (GUI) 构建等多个子步骤。为了加速开发过程，算法开发人员需要一个软件工具来辅助所有子步骤，以便他们能够专注于核心功能的实现。特别是对于深度学习 (DL) 算法的开发，非常需要一个支持训练数据标注和 GUI 构建的软件工具。在这项工作中，我们构建了 AnatomySketch，这是一个具有友好 GUI 和灵活插件接口的可扩展开源软件平台，用于集成用户开发的算法模块。通过插件接口，算法开发人员可以快速为临床验证创建基于 GUI 的软件原型。AnatomySketch 支持使用触笔和多点触摸屏幕进行图像标注。它还提供了高效的工具，便于人类专家和人工智能 (AI) 算法之间的协作。我们展示了四个示例应用，包括定制的 MRI 图像诊断、交互式肺叶分割、人机协作的脊柱椎间盘分割以及用于 DL 模型训练的 Annotation-by-iterative-Deep-Learning (AID)。使用 AnatomySketch，实验室原型和临床测试之间的差距得以弥合，医学图像分析算法的开发得以加速。该软件在 https://github.com/DlutMedimgGroup/AnatomySketch-Software 上开放。
