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Ultrasound image contrast enhancement via integrating transducer position information

机译:通过整合换能器位置信息来增强超声图像对比度

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Abstract: Computer-aided visualization and segmentation of structures of interest in ultrasound images require speckle noise reduction typically via lowpass filtering at the cost of blurring the edges. We have found that an advanced technique called 'sticks' algorithm, the possible locations of a reflector is modeled by a set of short line segments each with a different orientation. The goal is to select a particular stick out of the many different possible stick orientations, which best describes a reflector in the neighborhood. The original 'sticks' algorithm assumes that ultrasound echo could originate from a reflector positioned in any orientation with respect to the incident ultrasound beam, which is not a 100 percent valid assumption. Instead, for every possible reflector location in the image, we calculate the prior probability of different possible stick templates. Using Bayesian decision theory, we have integrated this additional information into the original sticks algorithm. The results indicate that similar to the original sticks algorithms, the speckles are reduced while preserving the edges in the image. In addition, the new sticks algorithm is faster than the original algorithm by a factor of 4.2. This approach is one of the few attempts in ultrasound image segmentation where the knowledge of the imaging process, such as the transducer position, has been incorporated for improved contrast enhancement. !24
机译:摘要:超声图像中感兴趣的结构的计算机辅助可视化和分割通常需要通过低通滤波来降低斑点噪声,但以模糊边缘为代价。我们发现一种称为“棒”算法的先进技术,可以通过一组短线段来模拟反射器的可能位置,每个短线段均具有不同的方向。目的是从许多可能的杆方向中选择一个特定的杆,从而最好地描述附近的反射器。原始的“棒”算法假设超声回声可能源自相对于入射超声束以任何方向定位的反射器,这并不是100%有效的假设。取而代之的是,对于图像中每个可能的反射器位置,我们计算出不同可能的棒状模板的先验概率。使用贝叶斯决策理论,我们已将此附加信息集成到原始的Sticks算法中。结果表明,与原始的棒算法相似,斑点得以减少,同时保留了图像中的边缘。此外,新的摇杆算法比原始算法快4.2倍。这种方法是超声图像分割中为数不多的尝试之一,其中已结合了成像过程的知识(例如换能器位置)来提高对比度。 !24

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