Segmentation of Medical Ultrasound Images using Active Contours

O. Michailovich, A. Tannenbaum
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引用次数: 24

Abstract

Segmentation of medical ultrasound images (e.g., for the purpose of surgical or radiotherapy planning) is known to be a difficult task due to the relatively low resolution and reduced contrast of the images, as well as due to the discontinuity and uncertainty of segmentation boundaries caused by speckle noise. Under such conditions, useful segmentation results seem to be only achievable by means of relatively complex algorithms, which are usually computationally involved and/or require a prior learning. In this paper, a different approach to the problem of segmentation of medical ultrasound images is proposed. In particular, we propose to preprocess the images before they are subjected to a segmentation procedure. The proposed preprocessing modifies the images (without affecting their anatomic contents) so that the resulting images can be effectively segmented by relatively simple and computationally efficient means. The performance of the proposed method is tested in a series of both in silico and in vivo experiments.
基于活动轮廓的医学超声图像分割
医学超声图像的分割(例如,用于手术或放疗计划)是一项艰巨的任务,因为图像的分辨率相对较低,对比度降低,以及由于散斑噪声引起的分割边界的不连续和不确定性。在这种情况下,有用的分割结果似乎只能通过相对复杂的算法来实现,这些算法通常涉及计算和/或需要事先学习。本文提出了一种不同的医学超声图像分割方法。特别是,我们建议在对图像进行分割之前对其进行预处理。所提出的预处理修改图像(不影响其解剖内容),使所得图像可以通过相对简单和计算效率高的手段进行有效分割。所提出的方法的性能在一系列的硅和体内实验中进行了测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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