Software Package for Automated Analysis of Lung Ultrasound Videos
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 19 references that are in the map. First posted on arXiv 1 Aug 2022.
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4 of 19 references.
References · 4
- 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,186
- 2017Deep Reinforcement Learning for Unsupervised Video Summarization with Diversity-Representativeness Rewardcited by 105
- 2022covEcho Resource constrained lung ultrasound image analysis tool for faster triaging and active learningcited by 2
- 2021Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imagingcited by 1
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