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MODELING THERMOGRAPHY OF THE TUMOROUS HUMAN BREAST: FROM FORWARD PROBLEM TO INVERSE PROBLEM SOLVING

机译:肿瘤人类乳房的造型热成像:从前向问题逆问题解决

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The abnormal thermogram has been shown to be a reliable indicator of a high risk of breast cancer. Nevertheless, a major weakness of current infrared breast thermography is its poor sensitivity for deeper tumors. Numerical modeling for breast thermography provides an effective tool to investigate the complex relationships between the breast thermal behaviors and the underlying pathophysiological conditions. Conventional "forward problem" modeling cannot be used to directly improve the tumor detectability, however, because the underlying tissue thermal properties are generally unknown. Based on our new comprehensive forward modeling, we propose an "inverse problem" modeling technique that aims to estimate tissue thermal properties from the breast surface thermogram. Our data suggest that the estimation of tumor-induced thermal contrast can be significantly improved by using the proposed inverse problem solving techniques to provide the individual-specific thermal background, especially for deeper tumors.
机译:异常的热分析图已被证明是乳腺癌高风险的可靠指标。然而,目前红外乳房热成像的主要弱点是对更深的肿瘤的敏感性差。乳房热成像的数值建模提供了一种有效的工具,用于研究乳房热行为与潜在病理生理病症之间的复杂关系。常规的“前进问题”模拟不能用于直接改善肿瘤可检测性,因为潜在的组织热性质通常是未知的。基于我们新的全面前进建模,我们提出了一种“逆问题”建模技术,旨在估计来自乳房表面热量图的组织热性能。我们的数据表明,通过使用所提出的逆问题求解技术来提供个体特异性的热背景,尤其是对于更深的肿瘤,可以显着改善肿瘤诱导的热对比度的估计。

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