超声图像中的斑点:是好是坏?

Nikhil S. Narayan, P. Marziliano, J. Kanagalingam, C. Hobbs
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引用次数: 9

摘要

与将斑点相关像素作为噪声处理并过滤超声图像以去除斑点噪声的流行观点相反,本研究工作研究了这些像素在执行甲状腺多器官分割中的实际重要性和使用。在这项工作中,斑点相关像素被划分为三个回声水平,然后用于将甲状腺的超声图像分割成气管、颈动脉、肌肉和甲状腺。介绍了新的技术来估计甲状腺的前边界使用低通滤波强度梯度的高回声散斑像素在横向和纵向超声扫描分别。定义了一个类似于活动轮廓模型的能量函数,使用低回声散斑像素对颈动脉进行分割。所提出的技术在88张甲状腺图像上执行。使用Dice系数作为重叠度量,通过测量与两位专家医生获得的Ground Truth分割的重叠程度,对32张甲状腺图像进行验证,确定使用斑点进行分割的临床意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speckle in ultrasound images: Friend or FOE?
Contrary to the popular belief of treating speckle related pixels as noise and filtering an ultrasound image for speckle noise removal, the practical importance and use of these pixels in performing a multi-organ segmentation of the thyroid gland is studied in this research work. In this work, speckle related pixels are classified into three echogenic levels and then used to segment an ultrasound image of the thyroid gland into the trachea, carotid, muscles and thyroid. Novel techniques are introduced to estimate the anterior boundaries of the thyroid gland using low pass filtered intensity gradients of the hyperechoic speckle pixels in transverse and longitudinal ultrasound scans, respectively. An energy functional similar to active contour models is defined to segment that carotid artery using hypoechoic speckle pixels. The proposed technique was executed on 88 images of the thyroid gland. Clinical significance of using speckles to segment is determined by validating on 32 images of the thyroid gland by measuring the overlap with the Ground Truth segmentation obtained from two expert doctors using Dice coefficient as the overlap measure.
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