Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound
University of Trento · Fondazione Bruno Kessler · +3 more institutions
Abstract
Deep learning (DL) has proved successful in medical imaging and, in the wake of the recent COVID-19 pandemic, some works have started to investigate DL-based solutions for the assisted diagnosis of lung diseases. While existing works focus on CT scans, this paper studies the application of DL techniques for the analysis of lung ultrasonography (LUS) images. Specifically, we present a novel fully-annotated dataset of LUS images collected from several Italian hospitals, with labels indicating the degree of disease severity at a frame-level, video-level, and pixel-level (segmentation masks). Leveraging these data, we introduce several deep models that address relevant tasks for the automatic analysis of LUS…
Citation impact
- FWCI
- 57.89
- Percentile
- 100%
- References
- 56
Authors
22Topics & keywords
- Computer science
- Artificial intelligence
- Deep learning
- Segmentation
- Pattern recognition (psychology)
- Medical imaging
- Frame (networking)
- Coronavirus disease 2019 (COVID-19)
- Good health and well-being