Whole Slide Images (WSIs) provide exceptional detail for studying tissue
architecture at the cell level. To study tumour microenvironment (TME) with the
context of various protein biomarkers and cell sub-types, analysis and
registration of features using multi-stained WSIs is often required.
Multi-stained WSI pairs normally suffer from rigid and non-rigid deformities in
addition to slide artefacts and control tissue which present challenges at
precise registration. Traditional registration methods mainly focus on global
rigid/non-rigid registration but struggle with aligning slides with complex
tissue deformations at the nuclei level. However, nuclei level non-rigid
registration is essential for downstream tasks such as cell sub-type analysis
in the context of protein biomarker signatures. This paper focuses on local
level non-rigid registration using a nuclei-location based point set
registration approach for aligning multi-stained WSIs. We exploit the spatial
distribution of nuclei that is prominent and consistent (to a large level)
across different stains to establish a spatial correspondence. We evaluate our
approach using the HYRECO dataset consisting of 54 re-stained images of H\&E
and PHH3 image pairs. The approach can be extended to other IHC and IF stained
WSIs considering a good nuclei detection algorithm is accessible. The
performance of the model is tested against established registration algorithms
and is shown to outperform the model for nuclei level registration.

本文以基于核定位的点集注册方法为基础，针对多染色 WSIs 进行局部非刚性注册，以实现核级别的分组分析和蛋白质标记的上下文分析，通过对 HYRECO 数据集进行评估并与其他已建立的注册算法进行比较，表明该方法在核级别的注册上具有优越性。