Fourier‐transform infrared (FTIR) microspectroscopy is rounding the corner to become a label‐free routine method for cancer diagnosis. In order to build infrared‐spectral based classifiers, infrared images need to be registered with Hematoxylin and Eosin (H&E) stained histological images. While FTIR images have a deep spectral domain with thousands of channels carrying chemical and scatter information, the H&E images have only three color channels for each pixel and carry mainly morphological information. Therefore, image representations of infrared images are needed that match the morphological information in H&E images. In this paper, we propose a novel approach for representation of FTIR images based on extended multiplicative signal correction highlighting morphological features that showed to correlate well with morphological information in H&E images. Based on the obtained representations, we developed a strategy for global‐to‐local image registration for FTIR images and H&E stained histological images of parallel tissue sections.

中文翻译：

---

红外显微图像的灰度表示，通过扩展的乘性信号校正可与组织学图像对齐。

傅里叶变换红外（FTIR）显微光谱技术即将成为一种无标签的癌症诊断常规方法。为了建立基于红外光谱的分类器，需要将红外图像与苏木精和曙红（H＆E）染色的组织学图像进行配准。虽然FTIR图像具有很深的光谱域，具有成千上万个承载化学和散射信息的通道，但是H＆E图像每个像素只有三个颜色通道，并且主要承载形态信息。因此，需要与H＆E图像中的形态信息相匹配的红外图像的图像表示。在本文中，我们提出了一种新的方法来表示FTIR图像，该方法基于扩展的倍增信号校正突出显示了形态特征，该特征与H＆E图像中的形态信息很好地相关。基于获得的表示，我们开发了针对平行组织切片的FTIR图像和H＆E染色的组织学图像进行全局到局部图像配准的策略。