Parametric optimization for tumour identification bioheat equation using ANOVA and the Taguchi method
Parametric optimization for tumour identification bioheat equation using ANOVA and the Taguchi method
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DOI：
10.1243/0954411001535534
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发表时间：
2000-01-01
期刊：
影响因子：
1.8
通讯作者：
Ng, EYK
中科院分区：
文献类型：
--
作者：
Sudharsan, NM;Ng, EYK
乳腺癌是女性第一号杀手疾病。众所周知，肿瘤的早期发现可以确保更好的预后和更高的生存率。本文开发了一种智能、廉价且非侵入性的诊断工具，用于帮助客观检测乳腺癌。该工具基于乳房表面的热成像扫描并结合使用生物热方程对乳房进行数值模拟。热成像扫描的医学应用利用皮肤温度作为潜在病理过程的指示。乳腺肿瘤上的热模式反映了血管对异常的反应。因此，异常的温度模式可能是潜在肿瘤的指标。确定了七个重要参数，并使用 2(n) 设计（n = 参数数量，7）进行方差分析 (ANOVA)。分析了各种参数的作用和重要性。基于上述2(7)设计，采用田口方法对参数进行优化，以确保来自肿瘤的信号与来自其他因素的噪声相比最大化。该模型预测，捕获肿瘤信号的理想环境是当患者处于基础代谢活动且在低温环境下皮下灌注相应较低时。
Breast cancer is the number one killer disease among women. It is known that early detection of a tumour ensures better prognosis and higher survival rate. In this paper an intelligent, inexpensive and non-invasive diagnostic tool is developed for aiding breast cancer detection objectively. This tool is based on thermographic scanning of the breast surface in conjunction with numerical simulation of the breast using the bioheat equation. The medical applications of thermographic scanning make use of the skin temperature as an indication of an underlying pathological process. The thermal pattern over a breast tumour reflects the vascular reaction to the abnormality. Hence an abnormal temperature pattern may be an indicator of an underlying tumour.Seven important parameters are identified and analysis of variance (ANOVA) is performed using a 2(n) design (n = number of parameters, 7). The effect and importance of the various parameters are analysed. Based on the above 2(7) design, the Taguchi method is used to optimize the parameters in order to ensure the signal from the tumour maximized compared with the noise from the other factors. The model predicts that the ideal setting for capturing the signal from the tumour is when the patient is at basal metabolic activity with a correspondingly lower subcutaneous perfusion in a low temperature environment.