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Echocardiography image enhancement using adaptive fractional order derivatives

机译:使用自适应分数阶导数的超声心动图图像增强

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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.
机译: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患者的健康状况。因此,图像增强是关键的预处理任务。本文提出了一种基于新兴的分数微积分的方法。提出的方法既简单又有效。在提出的算法中,首先使用每个像素的梯度大小将输入图像分为平滑区域,纹理区域和边缘区域。然后,选择适当顺序的分数差分掩模以增强每个像素。将该方法与最新的直方图均衡方法和固定阶分数微分方法进行了比较。对结果进行定量和定性验证。对于定量分析,使用平均梯度和熵。仿真结果验证了该方法的有效性。

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