ABSTRACT

Early detection of breast cancer will continue to be crucial in improving patient survival rates for the foreseeable future. Our long-term goal is to automate and refine the manual breast exam process using measured data on the breast surface in combination with formal inverse techniques to generate three-dimensional maps of the stiffness inside the breast tissue. In this paper, we report on computational techniques that use force measurements to create the stiffness map and validate the computational techniques experimentally with silicone tissue phantom experiments. We conducted 16 tests on tumour-free phantom samples and 16 tests on tumour-containing phantoms. Our stiffness mapping approach resulted in one false positive and a correct identification of the remaining 31/32 samples.

摘要

在可预见的未来，早期发现乳腺癌对于提高患者的存活率仍然至关重要。我们的长期目标是使用乳房表面的测量数据结合正式的逆向技术来自动化和改进手动乳房检查过程，以生成乳房组织内部硬度的三维图。在本文中，我们报告了使用力测量来创建刚度图的计算技术，并通过硅胶组织体模实验验证计算技术。我们对无肿瘤体模样本进行了 16 次测试，对含肿瘤体模进行了 16 次测试。我们的刚度映射方法导致了一个误报，并正确识别了剩余的 31/32 个样本。