Robot-assisted identification of breast tumor biomechanics

P. Yen, Hsiao-Ching Hsu, Yu-Ching Lin
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引用次数: 1

Abstract

There are increasing demands from physicians for providing modalities with second opinions, such as tumor hardness and mobility in the breast cancer diagnosis. Such system can improve the diagnosis accuracy and avoid unnecessary invasive biopsy through reducing the false positive cases. With such aim, we focused on complementing the ultrasound images with the biomechanics property of breast tumor so that the fused information can achieve this objective. In this paper, we utilize robot-automated inspection platform to acquire and characterize the mechanics data during palpating the breast tumor phantom. Subsequently a support vector regression model was constructed for describing tumor morphological mechanics model. The model has demonstrated its accuracy potentially to be applied in the future clinical applications.
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乳房肿瘤生物力学的机器人辅助识别
越来越多的医生要求提供第二意见,如乳腺癌诊断中的肿瘤硬度和活动度。该系统通过减少假阳性病例,提高了诊断的准确性,避免了不必要的侵入性活检。为此,我们致力于将超声图像与乳腺肿瘤的生物力学特性进行互补,使融合信息达到这一目的。在本文中,我们利用机器人自动检测平台来获取和表征乳腺肿瘤模体触诊过程中的力学数据。随后,构建支持向量回归模型来描述肿瘤的形态力学模型。该模型已证明其准确性,在未来的临床应用中具有潜在的应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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