Hospitals have accumulated a large amount of medical image data which need to be analyzed and integrated so as to be able to find the needed medical image in time, which is the basis of key technologies such as intelligent diagnosis of diseases. Meanwhile, through the analysis and integrated processing of medical images, the potential value of existing medical image data can be fully explored. In this paper, the key technologies in the intelligent image knowledge discovery system and the characteristics of medical image data are studied and improved.In this paper, the characteristics of knowledge discovery and medical image data are comprehensively considered, and RDM texture features are selected as the feature representation of medical images. An improved RDM operator is proposed and proved by experimental results. Experimental results show that the improved RDM coding method can improve the stability of medical image data expression.

中文翻译：

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医学影像智能知识发现与数据处理关键技术研究与应用

医院积累了大量的医学影像数据，需要对其进行分析和整合，以便及时找到需要的医学影像，这是疾病智能诊断等关键技术的基础。同时，通过对医学图像的分析和综合处理，可以充分挖掘现有医学图像数据的潜在价值。本文对智能图像知识发现系统中的关键技术和医学图像数据的特点进行了研究和改进。本文综合考虑知识发现和医学图像数据的特点，选取RDM纹理特征作为医学图像的特征表示。提出了一种改进的RDM算子，并通过实验结果证明。