运动的ROI提取通过抑制图像背景中的模糊和运动伪影来影响MR图像

C. Weerasinghe, L. Ji, H. Yan
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引用次数: 1

摘要

提出了一种提取被成像物体外边界包围的感兴趣区域的算法。虽然目前有许多算法可用于解决分割任务,但它们很容易被图像背景中的幽灵伪影和模糊所误导。为此,本文提出了一种两步背景清除算法。第一步包括选择运动影响最小的视图,使用熵最小化标准来抑制运动引起的模糊。第二步涉及使用模糊模型消除剩余的幽灵文物。这两个步骤都倾向于增加图像中暗像素的数量。轮廓提取采用改进的活动轮廓模型(snake)。将该方法应用于受旋转运动影响的自旋回波MR图像,取得了较好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ROI extraction from motion affected MR images by suppression of blurring and motion artifacts in the image background
An algorithm is presented for extraction of the region of interest (ROI) enclosed by the outer boundary of the imaged object. Although there are many algorithms presently available for solving segmentation tasks, they can be easily misled by the ghost artifacts and blurring in the background of the image. Therefore, a two step background-clearing algorithm is proposed in this paper. The first step involves selection of the least motion-affected views, using an entropy minimization criterion for suppression of motion induced blurs. The second step involves cancellation of the remaining ghost artifacts, using a fuzzy model. Both these steps tend to increase the number of dark pixels in the image. The contour extraction is performed using an improved active contour model (snake). The proposed method has been applied to spin echo MR images affected by rotational motion, producing good results.
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