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Breast thermography and pseudo-coloring presentation for improving gray infrared images

机译:乳房热成像和伪彩色显示,可改善灰色红外图像

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Breast cancer is the most common cancer in women (about 30% of all cancers). And is also the second common cancer after lung cancer. One woman out of eight develops breast cancer during lifetime. Breast thermography has a unique role in early detection of breast cancer and in this regards none of the other method such as mammography. The role of infrared imaging in early detection of breast cancer as an adjunct tool to mammography has been proved. Thermograms are usually provided in gray level images but Findings show gray images are not appropriate for human interpretation. Human beings can only discern a few dozen gray level values while they can distinguish thousands of colors. So In order to help thermologists to find abnormal regions in the thermograms, it's better to color thermograms. So pseudo-coloring of thermogram is one of the important factors for accurate diagnosis. In this research we offer comparing some common pseudo-coloring algorithm. Also a nonlinear function transform for pseudo-coloring of infrared breast images based on physiological properties of human eye is proposed, and it's efficiency is shown by experience.
机译:乳腺癌是女性中最常见的癌症(约占所有癌症的30%)。并且也是继肺癌之后的第二大常见癌症。八分之一的女性一生中会患乳腺癌。乳房热成像在乳腺癌的早期检测中具有独特的作用,在这方面,没有其他方法可以进行乳房X线照相。红外成像作为乳腺癌的辅助工具,在乳腺癌的早期检测中的作用已得到证明。通常在灰度图像中提供温度记录图,但调查结果显示灰度图像不适合人类解释。人类只能分辨几十个灰度值,而他们却可以分辨出数千种颜色。因此,为了帮助热科医生在温度记录图中发现异常区域,最好对温度记录进行着色。因此,热成像图的伪着色是准确诊断的重要因素之一。在这项研究中,我们提供了一些常见的伪着色算法的比较。提出了一种基于人眼生理特性的红外乳房图像伪彩色非线性函数变换方法,并通过经验证明了其有效性。

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