Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:3622-3625. doi: 10.1109/EMBC46164.2021.9629970.
Joint analysis of multiple biomarker images and tissue morphology is important for disease diagnosis, treatment planning and drug development. It requires cross-staining comparison among Whole Slide Images (WSIs) of immune-histochemical and hematoxylin and eosin (H&E) microscopic slides. However, automatic, and fast cross-staining alignment of enormous gigapixel WSIs at single-cell precision is challenging. In addition to morphological deformations introduced during slide preparation, there are large variations in cell appearance and tissue morphology across different staining. In this paper, we propose a two-step automatic feature-based cross-staining WSI alignment to assist localization of even tiny metastatic foci in the assessment of lymph node. Image pairs were aligned allowing for translation, rotation, and scaling. The registration was performed automatically by first detecting landmarks in both images, using the scale-invariant image transform (SIFT), followed by the fast sample consensus (FSC) protocol for finding point correspondences and finally aligned the images. The Registration results were evaluated using both visual and quantitative criteria using the Jaccard index. The average Jaccard similarity index of the results produced by the proposed system is 0.942 when compared with the manual registration.
联合分析多个生物标志物图像和组织形态对于疾病诊断、治疗计划和药物开发非常重要。它需要对免疫组织化学和苏木精和伊红（H&E）显微镜载玻片的全玻片图像（WSI）进行交叉染色比较。然而，在单细胞精度下自动、快速地对齐巨大的千兆像素 WSI 具有挑战性。除了在幻灯片准备过程中引入的形态变形外，不同染色之间的细胞外观和组织形态也存在很大差异。在本文中，我们提出了一种基于特征的两步自动交叉染色 WSI 对齐方法，以协助定位淋巴结评估中即使是微小的转移性焦点。允许平移、旋转和缩放来对齐图像对。首先使用尺度不变图像变换（SIFT）在两幅图像中检测地标，然后使用快速样本共识（FSC）协议找到点对应关系，并最终对齐图像，从而自动执行配准。使用 Jaccard 指数的视觉和定量标准评估配准结果。与手动配准相比，所提出系统产生的结果的平均 Jaccard 相似性指数为 0.942。
