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Efficient and Effective Ultrasound Image Analysis Scheme for Thyroid Nodule Detection

机译:甲状腺结节检测有效且有效的超声图像分析方案

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Ultrasound imaging of thyroid gland provides the ability to acquire valuable information for medical diagnosis. This study presents a novel scheme for the analysis of longitudinal ultrasound images aiming at efficient and effective computer-aided detection of thyroid nodules. The proposed scheme involves two phases: a) application of a novel algorithm for the detection of the boundaries of the thyroid gland and b) detection of thyroid nodules via classification of Local Binary Pattern feature vectors extracted only from the area between the thyroid boundaries. Extensive experiments were performed on a set of B-mode thyroid ultrasound images. The results show that the proposed scheme is a faster and more accurate alternative for thyroid ultrasound image analysis than the conventional, exhaustive feature extraction and classification scheme.
机译:甲状腺的超声成像提供了获取医疗诊断的宝贵信息的能力。本研究提出了一种用于分析纵向超声图像的新方案,其旨在有效且有效的甲状腺结节的计算机辅助检测。所提出的方案涉及两阶段:a)应用一种用于检测甲状腺腺体的边界的新算法,B)通过仅从甲状腺边界之间的区域提取的局部二元图案特征载体的分类检测甲状腺结节。在一组B模式甲状腺超声图像上进行广泛的实验。结果表明,该方案比传统的详尽特征提取和分类方案更快,更准确地替代甲状腺超声图像分析。

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