Artifact Detection in Lung Ultrasound: An Analytical Approach

Lung ultrasound is used to detect various artifacts in the lungs that support diagnosis of different conditions. There ongoing research automatic detection such using machine learning. We propose a solution uses analytical computer vision methods two types lung artifacts, namely A- and B-lines. evaluate proposed approach on POCUS dataset data acquired from hospital. show by Fourier transform, we can analyze images real-time classify videos with an accuracy above 70%. also method’s applicability for segmentation, showcasing its high success rate B-lines (89% accuracy) shortcomings A-line detection. then hybrid combination neural networks increase horizontal line detection, emphasizing pleura.