Automatic bubble detection with neural networks on post decompression frames

I. B. Parlak, S. Egi, A. Ademoglu, Costantino Balestra, P. Germonpré, A. Marroni, S. Aydın
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Abstract

Post decompression records in echocardiography are considered to detect micro bubbles and to survey unexplained decompression sickness which is commonly examined by standardized methods such as dive computers and tables. In this study, existent bubbles are detected on transthoracic echicardiografic frames recorded after recreational diving. Bubble detection is performed by Artificial Neural Networks which are trained using bubbles with different morphologies. We showed that bubbles would be detected on four cardiac chambers without image segmentation.
在解压后帧上用神经网络自动检测气泡
超声心动图中的减压后记录被认为是检测微气泡和调查无法解释的减压病,减压病通常通过标准化方法(如潜水电脑和桌子)进行检查。在本研究中,在休闲潜水后记录的经胸心电帧上检测到存在的气泡。气泡检测是由人工神经网络完成的,这些神经网络使用不同形态的气泡进行训练。结果表明,在不进行图像分割的情况下,可以在四个心室上检测到气泡。
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