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首页> 外文期刊>International Journal of Computers & Applications >COMPUTER-BASED NODULE MALIGNANCY RISK ASSESSMENT IN THYROID ULTRASOUND IMAGES
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COMPUTER-BASED NODULE MALIGNANCY RISK ASSESSMENT IN THYROID ULTRASOUND IMAGES

机译:甲状腺超声图像中基于计算机的结节病风险评估

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摘要

This paper presents a computer-based approach for detection, de-lineation, and malignancy risk assessment of thyroid nodules in ultrasound (US) images. The proposed approach is automatic and integrates processes for: the thyroid gland boundaries detection, the detection of nodular lesions within the thyroid gland, the delineation of the detected nodules, and the classification of thyroid nodules according to malignancy risk. These processes embed textural and shape feature vectors derived from the US images, as well as state-of-the-art medical image analysis and pattern recognition tools. The obtained classification performance, which is associated with automatic malignancy risk assessment, was evaluated by means of the receiver operating characteristic (ROC), demonstrating an area under curve (AUC) equal to 0.93. The quantification of the results shows that the proposed approach: (1) contributes to the objectifi-cation of the diagnostic process by the utilization of explicit image features, whereas it can provide the diagnosticians with a second opinion, (2) is applicable in clinical practice and could contribute to the reduction of false medical decisions.
机译:本文提出了一种基于计算机的方法,用于超声(US)图像中甲状腺结节的检测,勾画和恶性风险评估。所提出的方法是自动的,并且集成了以下过程:甲状腺边界检测,甲状腺内结节性病变的检测,所检测结节的描绘以及根据恶性风险对甲状腺结节的分类。这些过程嵌入了源自美国图像的纹理和形状特征向量,以及最先进的医学图像分析和模式识别工具。通过接收者操作特征(ROC)评估获得的与自动恶性肿瘤风险评估相关的分类性能,表明曲线下面积(AUC)等于0.93。结果的量化表明,所提出的方法:(1)通过利用显式图像特征有助于诊断过程的客观化,而它可以为诊断师提供第二种意见,(2)适用于临床实践,并可能有助于减少错误的医疗决定。

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