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Restoration of nuclear medicine images using a Kalman filtering a

机译:使用Kalman滤波恢复核医学图像

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Abstract: The discrepancy between diagnostic importance of nuclear medicine images and their quality and the predominating visual interpretation of the images demand quality improvements. Digital image restoration procedures are known for being capable to solve this problem considering both noise and blurring. In this paper we propose the application of a modified 2D Kalman filter for nuclear medicine images (SPECT). In addition to the special capability of processing instationary signals the Kalman filter offers a possibility for controlling the filtering effect in a convenient way. The Kalman filter is based on a state space approach subdividing the imaging process into image generation and image degradation processes. The tested filter operates adaptively by permanent identification of the image generation model. For adaptation to the human visual system the filtering effect is modified depending on image quality represented by the mean information density and the local image contents represented by a structure information. The appropriate filtering effect is determined by modifying filter parameters with a predefined piecewise linear characteristic curve. The both smoothing and structure enhancing effect of our Kalman filtering approach is demonstrated in numerous tests performed with SPECT phantom images and brain SPECT studies.!7
机译:摘要:核医学图像的诊断重要性与图像质量之间的差异以及图像的主要视觉解释之间需要质量改进。考虑到噪声和模糊,数字图像恢复程序能够解决该问题。在本文中,我们提出了一种改进的二维卡尔曼滤波器在核医学图像(SPECT)中的应用。除了具有处理平稳信号的特殊功能外,卡尔曼滤波器还提供了以方便的方式控制滤波效果的可能性。卡尔曼滤波器基于状态空间方法,将成像过程细分为图像生成和图像降级过程。经过测试的滤波器通过永久识别图像生成模型来自适应地运行。为了适应人类视觉系统,根据由平均信息密度表示的图像质量和由结构信息表示的局部图像内容来修改滤波效果。通过使用预定义的分段线性特性曲线修改滤波器参数来确定适当的滤波效果。我们的卡尔曼滤波方法的平滑效果和结构增强效果在通过SPECT幻像图像和大脑SPECT研究进行的大量测试中得到了证明!7

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