A tissue-specific adaptive texture filter for medical ultrasound images
A tissue-specific adaptive texture filter for medical ultrasound images
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DOI：
10.1016/j.ultrasmedbio.2005.05.008
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发表时间：
2005-09-01
影响因子：
2.9
通讯作者：
Govaert, P
中科院分区：
文献类型：
--
作者：
Stippel, G;Philips, W;Govaert, P
超声图像的解释仍然是一项艰巨的任务，不同医生的意见通常并不明确。因此，在计算机辅助诊断领域有越来越多的兴趣。在医学图像处理领域，计算机辅助诊断包括图像增强以促进视觉解释，受影响区域、器官和其他医学感兴趣区域的自动指示，自动测量和图像配准的性能。在这篇文章中，我们介绍了一种新的算法，超声图像增强，采用多元纹理分类器的基础上的共生矩阵，结合自适应纹理平滑滤波器，是用来增强视觉差异和改善健康的新生儿脑组织和脑室周围白质软化的组织之间的边界检测。为了进行定量比较，我们描绘了脑室周围白质软化症的影响区域与两个不同的活动轮廓处理前后的10个图像与建议的技术和几个斑点过滤器从文献中。因此获得的半自动描绘进行比较与人工描绘的一个pathatologist。在所有情况下，所提出的技术实现的平均描绘是更接近的手动专家描绘比当图像处理与其他技术。(c)2005年世界医学和生物学超声联合会。
The interpretation of ultrasound images remains a difficult task and the opinion of different doctors is generally not unequivocal. Therefore, there is a growing interest in the field of computer-aided diagnosis. In the field of medical image processing, computer-aided diagnosis includes image enhancement to facilitate visual interpretation, automatic indication of affected areas, organs and other regions of medical interest, the performance of automatic measurements and image registration. In this article, we introduce a new algorithm for ultrasound image enhancement that employs a multivariate texture classifier based on the co-occurrence matrix, which, in combination with an adaptive texture smoothing filter, is used to enhance the visual difference between and improve boundary detection between healthy neonatal brain tissue and tissue affected by periventricular leukomalacia. For a quantitative comparison, we delineate the periventricular leukomalacia-affected regions with two different active contours before and after processing 10 images with the proposed technique and several speckle filters from the literature. The semi-automatic delineations thus obtained are compared with the manual delineations of a neonatologist. In all cases, the average delineation achieved with the proposed technique is closer to that of the manual expert delineation than when the images are processed with the other techniques. (c) 2005 World Federation for Ultrasound in Medicine & Biology.