基于Tamura和小波特征的融合医学图像检索

N. Kumar, Y. Ravi Kumar
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引用次数: 0

摘要

近十年来,基于内容的图像检索(CBIR)是医学图像处理中一个新兴且具有挑战性的研究领域。医学图像检索发挥了检索过程的准确性,并且可以在检索过程中采用田村特征和小波特征相结合的方法对其进行修改。这个过程是计算所有图像之间的距离,并形成一个矩阵。将该方法投影为医学图像处理中的CBIR过程,在不同的数据集上计算不同的统计参数。以医学图像的实验结果为依据,对该方法的性能和有效性进行了验证。从不同的角度对混淆矩阵进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fusion-based Medical Image Retrieval using Tamura and Wavelet features
In the last ten years, Content-based image retrieval (CBIR) is an emerging and challenging research area in medical image processing. The medical Image retrieval plays the accuracy of the retrieval process and further can be modified by a method that combines tamura and wavelet features in the retrieving process. The process is having calculation of distance between all the images and forms a matrix. The proposed method is projected as a process of CBIR in medical image processing with different statistical parameter calculations on different datasets. With the evidence of experimental results on medical images, the performance and effectiveness of the method is measured. The confusion matrix is evaluated in different views.
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