Automatic Registration Of The Medical Images - T1- And T2-weighted MR Knee Images

P. Zarychta
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引用次数: 8

Abstract

This article shows a new method of the automatic registration of T1- and T2-weighted MR knee images. This method is based on the entropy and energy measures of fuzziness and can be used in localization process of cruciate ligament. First, two sequences (T1- and T2-weighted) are converted to a fuzzy representation. Then, the entropy and energy measures are employed in the NCC (normalized cross correlation) and GD (gradient difference) methods. The alignment based on energy and entropy fuzzy measures shows a significant improvement in comparison with the implementation of the original image
医学图像的自动配准- T1和t2加权MR膝关节图像
本文提出了一种新的T1和t2加权MR膝关节图像的自动配准方法。该方法基于模糊的熵和能量度量,可用于十字韧带的定位过程。首先,将两个序列(T1加权和t2加权)转换为模糊表示。然后,在归一化互相关(NCC)和梯度差(GD)方法中采用熵和能量度量。基于能量和熵模糊度量的对齐与原图像的实现相比有明显的改善
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