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论文类型：期刊论文

发表时间：2022-01-01

发表刊物：JOURNAL OF DIGITAL IMAGING

所属单位：[1] Dalian University of Technology [2] University of Jyvaskyla

刊物所在地：美国

学科门类：[1] Radiology, Nuclear Medicine & Medical Imaging

卷号：35

期号：6

页面范围：1623-1633

ISSN号：1618-727X

关键字：ei; medline; scopus; pubmed; scie; inspec;

摘要：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 haps://github.com/DlutMedimgGroup/AnatomySketch-Software.

DOI码：10.1007/s10278-022-00660-5

影响因子：4.4