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Computer-readable Image Markers for Automated Registration in Correlative Microscopy – “autoCRIM”

Lookup NU author(s): Jake Sheriff, Professor Ian Fletcher

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

We present a newly developed methodology using computer-readable fiducial markers to allow images from multiple imaging modalities to be registered automatically. This methodology makes it possible to correlate images from many surface imaging techniques to provide an unprecedented level of surface detail on a nanometre scale that no one technique can provide alone.This methodology provides the capability to navigate to specific areas of interest when transferring samples from machine to machine seamlessly. Then taking data acquired from scanning electron microscope (SEM), secondary ion mass spectrometry (SIMS), x-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM) and optical inspection tools and combining all the data acquired to then generate a 3D data representative model of a surface.


Publication metadata

Author(s): Sheriff J, Fletcher IW, Cumpson PJ

Publication type: Article

Publication status: Published

Journal: Ultramicroscopy

Year: 2021

Volume: 228

Print publication date: 01/09/2021

Online publication date: 24/05/2021

Acceptance date: 18/05/2021

Date deposited: 03/05/2022

ISSN (electronic): 0304-3991

Publisher: Elsevier

URL: https://doi.org/10.1016/j.ultramic.2021.113322

DOI: 10.1016/j.ultramic.2021.113322


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Funding

Funder referenceFunder name
EPSRC

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