使用比例不变特征变换(SIFT)和数字图像弹性断层扫描(DIET)进行乳腺癌筛查试验的分离模态分析

Mubashir Hussain, H. Rehman, Owais Nazir, A. Kashif, A. Hassan, Muhammad Awais Dildar
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引用次数: 1

摘要

数字图像弹性层析成像(DIET)是一种无创的早期乳腺癌检测和筛查方法。在DIET中,在应用基准标记后,在乳房表面施加机械振动,并使用五个数码相机拍摄图像以捕捉表面运动。对乳房未标记的表面进行尺度不变特征变换(SIFT),生成跟踪表面运动的参考点。采用分离模态分析,用标记对振动的频率和幅值响应进行了评价。SIFT特征用于检测刚度的变化,这是指肿瘤的存在和/或位置。这增加了运动数据,减少了检测癌性肿瘤的噪音。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Separate Modal Analysis using Scale Invariant Feature Transform (SIFT) with Digital Image Elasto Tomography (DIET) for breast cancer screening test
Digital Image Elasto Tomography (DIET) is noninvasive approach for detection and screening test of breast cancer at an early stage. In DIET mechanical vibrations are applied on the surface of breast after applying fiducial markers and images are taken to capture surface motion using five digital cameras. Applying Scale Invariant Feature Transform (SIFT) on the unmarked surface of the breast to produce reference points for tracking surface motion. Using Separate Modal Analysis frequency and amplitude response of oscillations are evaluated using markers. SIFT features are used to detect change in stiffness which refers to presence and/or location of tumor. This increases motion data and reduces noise for detection of cancerous tumours.
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