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ASSESSMENT OF ABNORMALITY PATTERNS ASSOCIATED WITH COVID-19 FROM X-RAY IMAGES

机译:从X射线图像评估与Covid-19相关的异常模式

摘要

Systems and methods for assessing a disease are provided. An input medical image in a first modality is received. Lungs are segmented from the input medical image using a trained lung segmentation network and abnormality patterns associated with the disease are segmented from the input medical image using a trained abnormality pattern segmentation network. The trained lung segmentation network and the trained abnormality pattern segmentation network are trained based on 1) synthesized images in the first modality generated from training images in a second modality and 2) target segmentation masks for the synthesized images generated from training segmentation masks for the training images. An assessment of the disease is determined based on the segmented lungs and the segmented abnormality patterns.
机译:提供了评估疾病的系统和方法。 接收第一模态中的输入医学图像。 使用培训的异常模式分割网络从输入的肺分割网络从输入的肺分割网络分段,与疾病相关联的异常模式从输入的异常模式分割网络中分段。 训练的肺分段网络和训练的异常模式分割网络基于1的培训,其在第二模态中的训练图像中生成的第一模态中的合成图像,以及用于从训练训练的训练分割掩模生成的合成图像的目标分段掩码 图片。 基于细分肺和分段的异常模式确定对疾病的评估。

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