Nuclei-Location Based Point Set Registration of Multi-Stained Whole Slide Images

Abstract: 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.