基于位平面算法的模糊c均值医学图像分类

P. Swarnalatha, B. Tripathy
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引用次数: 12

摘要

该研究在医学图像处理领域的图像分析意义中起着至关重要的作用,受到了现代许多研究者的重视。在基于域的图像中,对图像中被破坏部分的故障进行识别是必要的。在本文中,我们着重于开发一种更好的医学图像分类方法。我们的方法是基于一种新颖的模糊方法与位平面(FCMBP)算法的概念。采用位平面滤波方法对给定图像进行切片分类,找出给定图像的破坏区域。对切片后的图像进行归一化处理,并与模糊技术进行比较,以更好地对损坏部分进行分类和聚类。从而提取出进一步重建图像所需的控制点。通过仿真对位平面模糊方法的性能进行了评价,结果表明,与可达方法相比,该方法具有更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel fuzzy c-means approach with bit plane algorithm for classification of medical images
This study plays a vital role in the significance of the analysis of an image in medical image processing field, is gaining thought of many researchers in modern times. The recognition of faults present in the destroyed portion of an image is imperative for based field. In this paper, we focus at developing an approach for better classification of medical images. Our methodology is based on the concept of a novel fuzzy approach with bit plane (FCMBP) algorithm. The bit plane filtering method is used to slice the given image for classification to find out the destroyed region of the given image. The sliced image should be normalized with the old techniques and compared with the fuzzy technique for better classification and cluster of the spoiled portion. Thereby the control points have been extracted that are needed for further reconstruction of images. The performance of fuzzy approach with bit plane technique is evaluated using simulation and it is proved that our approach yields better results when compared to accessible methods.
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