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DEEP LEARNING MEDICAL SYSTEMS AND METHODS FOR IMAGE RECONSTRUCTION AND QUALITY EVALUATION

机译:用于图像重建和质量评估的深度学习医疗系统和方法

摘要

Methods and apparatus to automatically generate an image quality metric for an image are provided. An example method includes automatically processing a first medical image using a deployed learning network model to generate an image quality metric for the first medical image, the deployed learning network model generated from a digital learning and improvement factory including a training network, wherein the training network is tuned using a set of labeled reference medical images of a plurality of image types, and wherein a label associated with each of the labeled reference medical images indicates a central tendency metric associated with image quality of the image. The example method includes computing the image quality metric associated with the first medical image using the deployed learning network model by leveraging labels and associated central tendency metrics to determine the associated image quality metric for the first medical image.
机译:提供了自动生成图像的图像质量度量的方法和装置。示例方法包括使用部署的学习网络模型自动处理第一医学图像以生成用于第一医学图像的图像质量度量,该部署的学习网络模型是从包括培训网络的数字学习和改善工厂生成的,其中,培训网络使用一组具有多种图像类型的标记的参考医学图像来调节“参考”,其中与每个标记的参考医学图像相关联的标签指示与图像的图像质量相关的集中趋势度量。示例方法包括通过利用标签和相关联的集中趋势度量来确定用于第一医学图像的相关图像质量度量,从而使用部署的学习网络模型来计算与第一医学图像相关的图像质量度量。

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