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A two-step framework for the registration of HE stained and FTIR images

机译:用于记录HE染色和FTIR图像的两步框架

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摘要

FTIR spectroscopy is an emerging technology with high potential for cancer diagnosis but with particular physical phenomena that require special processing. Little work has been done in the field with the aim of registering hyperspectral Fourier-Transform Infrared (FTIR) spectroscopic images and Hematoxilin and Eosin (HE) stained histological images of contiguous slices of tissue. This registration is necessary to transfer the location of relevant structures that the pathologist may identify in the gold standard HE images. A two-step registration framework is presented where a representative gray image extracted from the FTIR hypercube is used as an input. This representative image, which must have a spatial contrast as similar as possible to a gray image obtained from the HE image, is calculated through the spectrum variation in the fingerprint region. In the first step of the registration algorithm a similarity transformation is estimated from interest points, which are automatically detected by the popular SURF algorithm. In the second stage, a variational registration framework defined in the frequency domain compensates for local anatomical variations between both images. After a proper tuning of some parameters the proposed registration framework works in an automated way. The method was tested on 7 samples of colon tissue in different stages of cancer. Very promising qualitative and quantitative results were obtained (a mean correlation ratio of 92.16% with a standard deviation of 3.10%).
机译:FTIR光谱学是一种新兴的技术,具有很高的癌症诊断潜力,但具有需要特殊处理的特殊物理现象。为了记录高光谱傅里叶变换红外(FTIR)光谱图像以及连续组织切片的苏木精和曙红(HE)染色的组织学图像,该领域的工作很少。必须进行此注册才能转移病理医生可以在黄金标准HE图像中识别的相关结构的位置。提出了两步配准框架,其中将从FTIR超立方体中提取的代表性灰度图像用作输入。通过指纹区域中的光谱变化来计算该代表性图像,该代表性图像必须具有与从HE图像获得的灰度图像尽可能相似的空间对比度。在配准算法的第一步中,根据兴趣点估算相似度变换,这些兴趣点由流行的SURF算法自动检测。在第二阶段,在频域中定义的变化配准框架将补偿两个图​​像之间的局部解剖结构变化。在适当调整某些参数之后,建议的注册框架将以自动化方式工作。该方法在癌症不同阶段的7个结肠组织样本上进行了测试。获得了非常有希望的定性和定量结果(平均相关率为92.16%,标准偏差为3.10%)。

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