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METHOD AND SYSTEM FOR EVALUATING QUALITY OF MEDICAL IMAGE DATASET FOR MACHINE LEARNING

机译:机器学习医学图像数据质量评估方法及系统

摘要

The present disclosure relates to a method for evaluating quality of a medical image dataset and a system thereof capable of confirming whether medical image data is suitable to be used for machine learning. Evaluation items may include data normality which means a ratio of normal frames in all frames; learning fitness which means a ratio of labeled or labelable frames in the received data; and anatomical completeness which means a ratio of anatomical elements included in the received data against anatomical elements based on medical standards.
机译:本公开涉及一种用于评估医学图像数据集的质量的方法及其系统,其能够确认医学图像数据是否适合用于机器学习。评估项目可以包括数据正常性,其意味着所有帧中正常帧的比率;学习适应性,指接收到的数据中带有标记或可标记帧的比率;解剖完整性是指接收数据中包含的解剖元素与基于医学标准的解剖元素之比。

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