In the recent past with the rapid surge of COVID-19 infections, lung ultrasound has emerged as a fast and powerful diagnostic tool particularly for continuous and periodic monitoring of the lung. There have been many attempts towards severity classification, segmentation and detection of key landmarks in the lung. Leveraging the progress, an automated lung ultrasound video analysis package is presented in this work, which can provide summary of key frames in the video, flagging of the key frames with lung infection and options to automatically detect and segment the lung landmarks. The integrated package is implemented as an open-source web application and available in the link https://github.com/anitoanto/alus-package.
翻译:最近,随着COVID-19感染的迅速激增,肺部超声波已成为一个快速和有力的诊断工具,特别是用于对肺部进行连续和定期监测的诊断工具,已多次尝试对肺部的关键里程碑进行严格分类、分解和检测,这项工作利用了进展,展示了一套自动肺部超声波视频分析包,可提供录像中关键框架的概要、肺部感染关键框架的标记以及自动检测肺部标志和截断这些标志的选项,综合包作为开放源网络应用程序实施,可在链接https://github.com/anitoanto/alus-package上查阅。