An Open-Source Whole Slide Image Registration Workflow at Cellular Precision Using Fiji, QuPath and Elastix

Author:

Chiaruttini Nicolas,Burri Olivier,Haub Peter,Guiet Romain,Sordet-Dessimoz Jessica,Seitz Arne

Abstract

Image analysis workflows for Histology increasingly require the correlation and combination of measurements across several whole slide images. Indeed, for multiplexing, as well as multimodal imaging, it is indispensable that the same sample is imaged multiple times, either through various systems for multimodal imaging, or using the same system but throughout rounds of sample manipulation (e.g. multiple staining sessions). In both cases slight deformations from one image to another are unavoidable, leading to an imperfect superimposition Redundant and thus a loss of accuracy making it difficult to link measurements, in particular at the cellular level. Using pre-existing software components and developing missing ones, we propose a user-friendly workflow which facilitates the nonlinear registration of whole slide images in order to reach sub-cellular resolution level. The set of whole slide images to register and analyze is at first defined as a QuPath project. Fiji is then used to open the QuPath project and perform the registrations. Each registration is automated by using an elastix backend, or semi-automated by using BigWarp in order to interactively correct the results of the automated registration. These transformations can then be retrieved in QuPath to transfer any regions of interest from an image to the corresponding registered images. In addition, the transformations can be applied in QuPath to produce on-the-fly transformed images that can be displayed on top of the reference image. Thus, relevant data can be combined and analyzed throughout all registered slides, facilitating the analysis of correlative results for multiplexed and multimodal imaging.

Publisher

Frontiers Media SA

Subject

General Medicine

Reference15 articles.

1. Introduction to Digital Image Analysis in Whole-Slide Imaging: A white Paper from the Digital Pathology Association;Aeffner;J. Pathol. Inform.,2019

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3. Robust Registration of Calcium Images by Learned Contrast Synthesis;Bogovic,2016

4. ANHIR: Automatic Non-rigid Histological Image Registration Challenge;Borovec;IEEE Trans. Med. Imaging,2020

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