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Segmentation of Medical Ultrasound Images using Active Contours

机译:使用活动轮廓的医学超声图像分割

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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.
机译:已知医疗超声图像的分割(例如,用于外科或放射治疗计划的目的)是由于相对较低的分辨率和图像对比度降低,以及由于分割边界的不连续性和不确定度导致的困难的任务通过斑点噪音。在这种条件下,有用的分段结果似乎仅通过相对复杂的算法来实现,这通常是在计算上涉及和/或需要先前学习的。在本文中,提出了一种不同的医学超声图像分割问题的方法。特别是,我们建议在对其进行分割过程之前预处理图像。所提出的预处理修改图像(不影响其解剖内容),使得可以通过相对简单和计算的有效手段有效地分割所得到的图像。所提出的方法的性能在硅和体内实验中在一系列中进行测试。

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