超声心动图图像增强使用自适应分数阶导数

Ayesha Saadia, A. Rashdi
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引用次数: 9

摘要

医学超声图像本质上是低对比度的。医生需要有关组织和其他重要结构的信息来评估病人的健康状况。因此,图像增强是一项关键的预处理任务。本文提出了一种基于分数阶微积分这一新兴课题的方法。该方法简单有效。该算法首先利用每个像素的梯度大小将输入图像划分为光滑区、纹理区和边缘区。然后选择适当的分数阶差分掩模顺序来增强每个像素。将该方法与最先进的直方图均衡化方法和定阶分数阶微分方法进行了比较。结果进行了定量和定性验证。定量分析采用平均梯度和熵。仿真结果验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Echocardiography image enhancement using adaptive fractional order derivatives
Medical ultrasound images are low contrast in nature. Information regarding tissues and other important structure is required by a physician to assess patient's health. Therefore image enhancement is a critical pre-processing task. In this paper a methodology based on emerging topic of fractional calculus is proposed. Proposed method is simple yet effective. In the proposed algorithm, input image is first divided into smooth, texture and edge regions using gradient magnitude of each pixel. Then appropriate order of fractional differential mask is selected to enhance each pixel. Proposed method is compared with state-of-the-art histogram equalization method and fixed-order fractional differential methods. Results are verified quantitatively and qualitatively. For quantitative analysis average gradient and entropy are used. Simulation results verify the effectiveness of proposed method.
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