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Content Based Medical Image Retrieval System Based on Generalized Gamma Distribution and Feature Matching Methodology

机译:基于广义伽玛分布和特征匹配方法的基于内容的医学图像检索系统

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摘要

Medical imaging is an area of image processing which concerns about the study of diseases. Medical imaging technologies have been improved significantly as a result of recent technological developments. However, these developments could not reach the level of expectations due to the lack of efficient radiologists and Specialized Doctors at remote areas, which in turn became a problem of concern for identifying the diseases and imparting the treatment to the patients residing at remote areas. This paper addresses the issue by presenting an approach for delivering effective treatment to the people living at rural regions using Content Based Medical Image Retrieval (CBMIR) system. The results derived are tested using metrics like Precision and Recall. The relevant images retrieved based on the developed model are evaluated for efficiency using Quality metrics and are compared with that of the existing models based on the Gaussian Mixture Model and Skew Gaussian Mixture model.
机译:医学成像是涉及疾病研究的图像处理领域。由于最近的技术发展,医学成像技术已得到显着改善。然而,由于缺乏有效的放射科医生和偏远地区的专科医生,这些进展无法达到预期的水平,这反过来成为确定疾病并为偏远地区的患者提供治疗的关注问题。本文通过提出一种使用基于内容的医学图像检索(CBMIR)系统为农村地区的人们提供有效治疗的方法来解决这一问题。使用Precision和Recall等指标测试得出的结果。使用质量度量对基于开发的模型检索的相关图像进行效率评估,并将其与基于高斯混合模型和偏高斯混合模型的现有模型进行比较。

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