Abstract
In this paper, we present a fast method for registration of multiple large, digitised whole-slide images (WSIs) of serial histology sections. Through cross-slide WSI registration, it becomes possible to select and analyse a common visual field across images of several serial section stained with different protein markers. It is, therefore, a critical first step for any downstream co-localised cross-slide analysis. The proposed registration method uses a two-stage approach, first estimating a fast initial alignment using the tissue sections’ external boundaries, followed by an efficient refinement process guided by key biological structures within the visual field. We show that this method is able to produce a high quality alignment in a variety of circumstances, and demonstrate that the refinement is able to quantitatively improve registration quality. In addition, we provide a case study that demonstrates how the proposed method for cross-slide WSI registration could be used as part of a specific co-expression analysis framework.
Highlights
A major challenge for automated multi-slide analysis is that sectioning the sample destroys the 3-dimensional structure, and the continuity of the tissue in the z-axis
Section registration this condition is key because it is likely that some of the tissue structures will not persist across multiple sections and cannot be used for alignment, this is the case in part due to the section thickness being of a similar order to the depth of the structures themselves
We have evaluated the quality of the registration across a set of 10 cases, each containing several serial sections to be registered
Summary
A major challenge for automated multi-slide analysis is that sectioning the sample destroys the 3-dimensional structure, and the continuity of the tissue in the z-axis. This means that any co-localised cross-slide analysis is impossible without first re-aligning, or registering, the images. We present a novel framework for robust registration of serial sections stained with different markers, enabling many forms of cross-slide analysis such as localised co-expression tasks. Using this software, we demonstrate how the proposed framework may be applied to a specific cross-slide analysis task by providing experimental results of both the registration algorithm and its application to ER/PR scoring. We will detail the individual components of the serial section registration algorithm; an approximate alignment on the external boundaries of the tissue sections and a refinement stage using the sections’ internal tissue structures
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