Fast Adaptive Anisotropic Filtering for Medical Image Enhancement

J. George, S.P. Indu
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引用次数: 16

Abstract

In this paper, local structure tensor (LST) based adaptive anisotropic filtering (AAF) methodology is used for medical image enhancement over different modalities. This filtering framework enhances and preserves anisotropic image structures while suppressing high-frequency noise. The goal of this work is to reduce the overall computational cost with minimum risk on accuracy by introducing optimized filternets for local structure analysis and reconstruction filtering. This filtering technique facilitates user interaction and direct control over high frequency contents of the signal. The efficacy of the filtering framework is evaluated by testing the system with medical images of different modalities. The results are compared using three different quality measures. Experimental results show that a good level of noise reduction along with structure enhancement can be achieved in the adaptively filtered images.
快速自适应各向异性滤波医学图像增强
本文将基于局部结构张量(LST)的自适应各向异性滤波(AAF)方法用于不同模态的医学图像增强。该滤波框架在抑制高频噪声的同时增强并保留了各向异性图像结构。本工作的目标是通过引入优化的滤波器来进行局部结构分析和重建滤波,在降低总体计算成本的同时降低精度风险。这种滤波技术便于用户交互和直接控制信号的高频内容。通过对不同模式的医学图像进行测试,评估了过滤框架的有效性。使用三种不同的质量测量方法对结果进行比较。实验结果表明,自适应滤波后的图像具有较好的降噪效果和结构增强效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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