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Content-based retrieval of biomedical images using orthogonal Fourier-Mellin moments

机译:使用正交傅里叶-梅林矩基于内容的生物医学图像检索

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Biomedical imaging field is growing enormously from last decade. The medical images have been used and stored continuously for diagnosis as well as research purposes. For real-time retrieval of medical images from such storage repositories, there is a grave need of an effective and efficient biomedical image indexing and retrieval approach. In this quest, this paper presents a new approach for the retrieval of CT and MR images using orthogonal Fourier-Mellin moments (OFMMs). OFMMs have excellent information representation capability that enables them to pack the entire image information in very less number of coefficients. This property makes the proposed approach not only effective but also computationally very efficient and most favourable among all the existing approaches. The proposed approach has been tested and compared with numerous existing, state-of-the-art as well as recently published biomedical indexing and retrieval approaches on two standard databases namely, NEMA CT and NEMA MRI. Additional experiments have been conducted to analyse the noise robustness ability of the proposed and all the compared approaches. The reported results show superior retrieval performance of the proposed approach and a significant increase in the retrieval rate over all the existing approaches on noisy images on both the test databases.
机译:从最近的十年开始,生物医学成像领域正在迅速发展。医学图像已被连续使用和存储以用于诊断和研究目的。为了从这样的存储库实时检索医学图像,迫切需要一种有效的生物医学图像索引和检索方法。在此任务中,本文提出了一种使用正交傅里叶-梅林矩(OFMM)检索CT和MR图像的新方法。 OFMM具有出色的信息表示能力,使它们能够以很少的系数打包整个图像信息。这种特性使所提出的方法不仅有效,而且在计算上也非常有效,并且在所有现有方法中都是最有利的。已对提议的方法进行了测试,并将其与两个标准数据库(即NEMA CT和NEMA MRI)上现有的许多最新技术以及最近发布的生物医学索引和检索方法进行了比较。已经进行了其他实验来分析所提出的方法和所有比较方法的噪声鲁棒性。报告的结果表明,在两个测试数据库的噪声图像上,所提出方法的检索性能均优于所有现有方法,并且检索率显着提高。

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