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Approach to estimating low contrast inclusion with a priori guidance

机译:用先验指导估算低对比度纳入的方法

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Near-infrared diffuse optical tomography (NIR DOT) for noninvasive tissue monitoring have been developed for nearly two decades. The NIR imaging, however, suffers from low resolution due to the diffusive nature of the scattered light; there are compelling reasons for merging high-resolution structural information from other imaging modalities with the functional information attainable with NIR DOT. In this article, slight variation of the inclusion (tumor) in low contrast of optical properties is estimated and investigated. We present that an initial study of using a structural a prioriknowledge in NIR tomography where absorption image reconstruction of the tested phantom is well defined with the aid of a structural a priori knowledge obtained from other imaging modalities. This is advantageous compared to either modality alone. As well, the reconstructed optical absorption coefficient is achieved more accurate near to be exact value with incorporating the empirical updating information being proportional to the off-boundary distance but not size of inclusion against the background. Numerical simulation is demonstrated on varied sizes, locations and contrast of the inclusion. With the comparison between with or without a priori and empirical updating information, it is found that the reconstructed optical properties are more accurate than the near-infrared imaging alone.
机译:对于近二十年来开发了非侵入式组织监测的近红外漫射光学断层扫描(NIR点)。然而,由于散射光的扩散性质,NIR成像遭受了低分辨率;有令人讨厌的原因,用于将高分辨率结构信息与其他成像方式合并,具有达到NIR点的功能信息。在本文中,估计和研究了含有低对比度的含有(肿瘤)的略微变化。我们认为,在NIR层析成像中使用结构A优先考虑的初步研究,其中借助于从其他成像方式获得的特性知识的结构优质地定义了测试的幻像的吸收图像重建。与单独的无论是一种方式相比,这是有利的。同样,重建的光学吸收系数是更精确的近的近似,与结合与偏远距离成比例但不包含在背景的夹杂物的大小的实证更新信息附近进行精确值。在包含的不同尺寸,位置和对比度上证明了数值模拟。随着与经验和经验更新信息之间的比较,发现重建的光学性质比单独的近红外成像更精确。

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