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首页> 外文会议>SPIE Conference on Biomedical Applications in Molecular, Structural, and Functional Imaging >Toward Understanding the Complex Mechanisms behind BreastThermography: An Overview for Comprehensive Numerical Study
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Toward Understanding the Complex Mechanisms behind BreastThermography: An Overview for Comprehensive Numerical Study

机译：了解培训背后的复杂机制：综合数值研究概况

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摘要

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 patho-physiological conditions. We have developed a set of new modeling techniques to take into account some subtle factors usually ignored in previous studies, such as gravity-induced elastic deformations of the breast, nonlinear elasticity of soft tissues, and dynamic behavior of thermograms. Conventional "forward problem" modeling cannot be used directly to improve tumor detectability, however, because the underlying tissue thermal properties are generally unknown. Therefore, we propose an "inverse problem" modeling technique that aims to estimate the tissue thermal properties from the breast surface thermogram. Our data suggest that the estimation of the tumor-induced thermal contrast can be improved significantly by using the proposed inverse problem solving techniques to provide the individual-specific thermal background, especially for deeper tumors. We expect the proposed new methods, taken together, to provide a stronger foundation for, and greater specificity and precision in, thermographic diagnosis, and treatment, of breast cancer.
机译：异常热已被证明是乳腺癌的高风险的可靠指标。然而，目前的红外乳腺热成像的主要弱点是其更深层次的肿瘤敏感性差。对于乳房热成像数值建模提供调查乳房的热行为和下面的病理生理条件之间的复杂关系的有效工具。我们已经制定了一套新的建模技术来考虑，通常在以往的研究，如乳房的重力引起的弹性变形，软组织的非线性弹性和热分析动态行为忽略一些微妙的因素。常规的“向前问题”建模不能直接用于然而，以改善肿瘤检测性，因为下面的组织的热性质通常是未知的。因此，我们提出了一种“逆问题”建模技术，其目的是估算从乳房表面热组织的热特性。我们的数据表明的肿瘤诱导的热反差的估计可以通过使用所提出的逆问题的解决的技术来提供对个体特异性热背景，特别是对更深的肿瘤显著改善。我们预计拟议的新方法，结合在一起，提供了一个坚实的基础，和更大的特异性和精度，热的诊断和治疗，乳腺癌。

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