a robust co-localisation measurement utilising z-stack image intensity similarities for biological studies一个健壮的co-localisation测量生物研究利用z-stack图像强度相似之处.pdfVIP

A Robust Co-Localisation Measurement Utilising Z-Stack Image Intensity Similarities for Biological Studies 1 2 1 2 1 Yinhai Wang *, Craig Ledgerwood , Claire Grills , Denise C. Fitzgerald *, Peter W. Hamilton 1 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, United Kingdom, 2 Centre for Infection and Immunity, Queen’s University Belfast, Belfast, United Kingdom Abstract Background: Co-localisation is a widely used measurement in immunohistochemical analysis to determine if fluorescently labelled biological entities, such as cells, proteins or molecules share a same location. However the measurement of co- localisation is challenging due to the complex nature of such fluorescent images, especially when multiple focal planes are captured. The current state-of-art co-localisation measurements of 3-dimensional (3D) image stacks are biased by noise and cross-overs from non-consecutive planes. Method: In this study, we have developed Co-localisation Intensity Coefficients (CICs) and Co-localisation Binary Coefficients (CBCs), which uses rich z-stack data from neighbouring focal planes to identify similarities between image intensities of two and potentially more fluorescently-labelled biological entities. This was developed using z-stack images from murine organotypic slice cultures from central nervous system tissue, and two sets of pseudo-data. A large amount of non-specific cross-over situations are excluded using this method. This proposed method is also proven to be robust in recognising co- localisations even when images are polluted with a range of noises. Results: The proposed CBCs and CICs produce robust co-localisation measurements which are easy to interpret, resilient to noise and capa