基于纹理分析方法的甲状腺肿瘤超声图像TIRADS分类

Aslan Berk Tüzüner, ve Osman Eroğul, G. Atac, V. Er
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引用次数: 0

摘要

甲状腺肿瘤是医学影像学观察的常见病。超声检查是最常用的诊断方法。为了确定肿瘤是良性的还是恶性的,有经验的医生使用各种技术。采用细针穿刺活检及随访检查确定肿瘤类型。然而,这些方法既耗时又增加了医生的工作量。因此,他们创建了一个风险分层系统称为ACR-TIRADS。该系统的缺点是主观性强,对于多发肿瘤,需要分析多种特征,耗时长。为了减轻医生的工作量,帮助他们获得更客观的分类,在本研究中,我们用纹理分析的方法对甲状腺肿瘤进行分类,并尝试将其分类到其TIRADS类。结果表明,灵敏度提高%82.8,精密度提高%85,准确度提高%73.0。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Ultrasonographic Thyroid Tumor Images to TIRADS Categories via Texture Analysis Methods
Thyroid tumors frequently observed disease by using medical imaging methods. Ultrasonography is the most frequently performed method for diagnosis. To determine, tumor is benign or malign, experienced doctors use various techniques. Fine needle aspiration biopsy and follow-up checking are used for determining type of tumor. However, these methods are time consuming and increasing work load of doctors. So, they created a risk stratification system which has called as ACR-TIRADS. Downside of this system is being subjective and for multiple tumors, it will be time consuming due to analyzing multiple features. To ease, doctors work load and help them to obtain more objective classification, on this study we worked thyroid tumors with texture analysis methods and tried to classify them, to their TIRADS classes. As the result of this study, sensitivity found up %82.8, precision %85 and accuracy found up %73.0.
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