AnatomySketch: An Extensible Open-Source Software Platform for Medical Image Analysis Algorithm Development.
AnatomySketch: An Extensible Open-Source Software Platform for Medical Image Analysis Algorithm Development.
复制标题
DOI：
10.1007/s10278-022-00660-5
复制
发表时间：
2022-12
影响因子：
4.4
通讯作者：
Kettunen, Lauri
中科院分区：
文献类型：
--
作者：
Zhuang, Mingrui;Chen, Zhonghua;Wang, Hongkai;Tang, Hong;He, Jiang;Qin, Bobo;Yang, Yuxin;Jin, Xiaoxian;Yu, Mengzhu;Jin, Baitao;Li, Taijing;Kettunen, Lauri
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协助所有子步骤，以便他们可以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，非常需要支持训练数据注释和GUI构建的软件工具。在这项工作中，我们构建了AnatomySketch，一个可扩展的开源软件平台，具有友好的GUI和灵活的插件接口，用于集成用户开发的算法模块。通过插件界面，算法开发人员可以快速创建基于GUI的软件原型，用于临床验证。AnatomySketch支持使用手写笔和多点触摸屏进行图像注释。它还提供了有效的工具，以促进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性应用，包括定制的MRI图像诊断，交互式肺叶分割，人类-AI协作的脊柱椎间盘分割和用于DL模型训练的迭代深度学习注释（AID）。使用AnatomySketch，弥合了实验室原型设计和临床测试之间的差距，并加速了MIA算法的开发。该软件在www.example.com上打开。在线版本包含补充材料，可通过10.1007/s10278 - 022 - 00660 - 5获得。
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. The online version contains supplementary material available at 10.1007/s10278-022-00660-5.
登录
查看更多内容
影响因子：
11.2
作者：
van Griethuysen JJM;Fedorov A;Parmar C;Hosny A;Aucoin N;Narayan V;Beets-Tan RGH;Fillion-Robin JC;Pieper S;Aerts HJWL
通讯作者：
Aerts HJWL
影响因子：
3.5
作者：
Shamonin DP;Bron EE;Lelieveldt BP;Smits M;Klein S;Staring M;Alzheimer's Disease Neuroimaging Initiative
通讯作者：
Alzheimer's Disease Neuroimaging Initiative
影响因子：
10.6
作者：
Gibson E;Giganti F;Hu Y;Bonmati E;Bandula S;Gurusamy K;Davidson B;Pereira SP;Clarkson MJ;Barratt DC
通讯作者：
Barratt DC
DOI：
10.1109/embc.2016.7591443
发表时间：
2016-08
期刊：
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
影响因子：
--
作者：
Yushkevich PA;Yang Gao;Gerig G
通讯作者：
Gerig G
影响因子：
5.6
作者：
Alexander DL;Tropsha A;Winkler DA
通讯作者：
Winkler DA