COMPUTER-AIDED DIAGNOSIS FOR THYROID GRAVES' DISEASE IN ULTRASOUND IMAGES
COMPUTER-AIDED DIAGNOSIS FOR THYROID GRAVES' DISEASE IN ULTRASOUND IMAGES
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DOI：
10.4015/s1016237210001815
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发表时间：
2010-04-01
影响因子：
0.9
通讯作者：
Shih, Shyang-Rong
中科院分区：
文献类型：
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作者：
Chang, Chuan-Yu;Liu, Hsiang-Yi;Shih, Shyang-Rong
甲亢是一种常见的甲状腺疾病。Graves病是最常见的病因之一，占甲状腺功能亢进症的70%-80%。在临床诊断中，医生通常使用超声(US)图像进行检查。不幸的是，他们不能直接根据美国的图像来决定格雷夫斯病，只能依靠血液测试来确定。验血通常需要几周时间才能得到检查结果。因此，在本文中，我们提出了一种直接在超声图像上诊断Graves病的方法。自动诊断满足短时间检查，患者可以快速了解自己的情况。我们对甲状腺区域进行分割，并利用一种高性能的分类器(支持向量机-支持向量机)对区域进行分类。格雷夫斯病是通过对分类区域的面积测量来诊断的。实验结果表明了该方法的有效性。
Hyperthyroidism is a common thyroid disease. Graves' disease is one of the most common etiologies with 70-80% of hyperthyroidism. In clinical diagnosis, physicians generally utilize ultrasound (US) images for inspections. Unfortunately, they are not able to decide the Graves' disease directly on the US images, and have to rely on blood tests to assure it. The blood tests often take weeks to obtain the inspection results. Hence, in this article, we proposed an approach to diagnose Graves' disease on US image directly. The automatic diagnosis meets a short-time inspection, and patients may know their situation quickly. We segment the thyroid regions and utilize a high-performance classifier (support vector machine - SVM) to classify the regions. The Graves' disease is diagnosed using an area measure on the classified regions. Experimental results show effectiveness of the proposed approach.