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A new approach for content-based image retrieval for medical applications using low-level image descriptors

机译:利用低级图像描述函数的医学应用程序基于内容的图像检索方法

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Content based image retrieval (CBIR) has become an important factor in medical imaging research and is obtaining a great success. More applications still need to be developed to get more powerful systems for better image similarity matching, and as a result getting better image retrieval systems. This research focuses on implementing low-level descriptors to maximize the quality of the retrieval of medical images. Such a research is supposed to set a better result in terms of image similarity matching. In this research a system that uses low-level descriptors is introduced. Three descriptors have been developed and applied in an attempt to increase the accuracy of image matching. The final results showed a qualified system in medical images retrieval specially that the low-level image descriptors have not been used yet in the image similarity matching in the medical field.
机译:基于内容的图像检索(CBIR)已成为医学成像研究的重要因素,并获得巨大成功。需要开发更多应用程序以获得更强大的系统以获得更好的图像相似性匹配,结果越来越好,可以获得更好的图像检索系统。本研究侧重于实施低级描述符,以最大限度地提高医学图像检索的质量。这种研究应该在图像相似性匹配方面设定更好的结果。在本研究中,介绍了使用低级描述符的系统。已经开发出三个描述符并应用了增加图像匹配的准确性。最终结果在医学图像中显示了一个合格的系统,特别是尚未在医学领域的图像相似性匹配中使用低级图像描述符。

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