Fusion for registration of medical images - a study

Rajiv Kapoor, Aditya Dutta, D. Bagai, T. Kamal
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引用次数: 15

Abstract

The paper is a study demonstrating the application of discrete multiwavelets in medical image registration. The idea is to improve the image content by fusing images like MRI, CT and SPECT images, so as to provide more information to the doctor. The process of fusion is not new but here the results of study have been compared with the results from FCM algorithm used for similar application. Multiwavelets have been used for better clustering, as their decomposition results were better than Daubechies decomposition. A new feature based fusion algorithm has been used. This method shows results better than other methods for image registration when the images have been taken for the same person at a particular angle. The selective fusion not only gives more information but also helps in disease detection.
融合配准医学图像的研究
本文研究了离散多小波在医学图像配准中的应用。其想法是通过融合MRI、CT和SPECT图像来改善图像内容,从而为医生提供更多的信息。融合的过程并不新鲜,但这里的研究结果与FCM算法在类似应用中的结果进行了比较。由于多小波的分解效果优于多贝希分解,因此聚类效果较好。采用了一种新的基于特征的融合算法。当从特定角度对同一个人进行图像配准时,该方法的配准效果优于其他方法。选择性融合不仅提供了更多的信息,而且有助于疾病的检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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