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Resolution limit of image analysis algorithms

Resolution limit of image analysis algorithms
Resolution limit of image analysis algorithms
The resolution of an imaging system is a key property that, despite many advances in optical imaging methods, remains difficult to define and apply. Rayleigh’s and Abbe’s resolution criteria were developed for observations with the human eye. However, modern imaging data is typically acquired on highly sensitive cameras and often requires complex image processing algorithms to analyze. Currently, no approaches are available for evaluating the resolving capability of such image processing algorithms that are now central to the analysis of imaging data, particularly location-based imaging data. Using methods of spatial statistics, we develop a novel algorithmic resolution limit to evaluate the resolving capabilities of location-based image processing algorithms. We show how insufficient algorithmic resolution can impact the outcome of location-based image analysis and present an approach to account for algorithmic resolution in the analysis of spatial location patterns.
1-12
Cohen, Edward A.K.
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Abraham, Anish V.
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Ramakrishnan, Sreevidhya
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Ober, Raimund J.
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Cohen, Edward A.K.
df5112ce-f48a-4e1f-b7de-4e7d6fbc7cf8
Abraham, Anish V.
4f71ee5b-b0b1-4e0e-8f64-5cea9ae8f0e0
Ramakrishnan, Sreevidhya
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Ober, Raimund J.
31f4d47f-fb49-44f5-8ff6-87fc4aff3d36

Cohen, Edward A.K., Abraham, Anish V., Ramakrishnan, Sreevidhya and Ober, Raimund J. (2019) Resolution limit of image analysis algorithms. Nature Communications, 10, 1-12. (doi:10.1038/s41467-019-08689-x).

Record type: Article

Abstract

The resolution of an imaging system is a key property that, despite many advances in optical imaging methods, remains difficult to define and apply. Rayleigh’s and Abbe’s resolution criteria were developed for observations with the human eye. However, modern imaging data is typically acquired on highly sensitive cameras and often requires complex image processing algorithms to analyze. Currently, no approaches are available for evaluating the resolving capability of such image processing algorithms that are now central to the analysis of imaging data, particularly location-based imaging data. Using methods of spatial statistics, we develop a novel algorithmic resolution limit to evaluate the resolving capabilities of location-based image processing algorithms. We show how insufficient algorithmic resolution can impact the outcome of location-based image analysis and present an approach to account for algorithmic resolution in the analysis of spatial location patterns.

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s41467-019-08689-x - Version of Record
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Accepted/In Press date: 9 January 2019
e-pub ahead of print date: 15 February 2019

Identifiers

Local EPrints ID: 428518
URI: https://eprints.soton.ac.uk/id/eprint/428518
PURE UUID: 8c0fb2e4-8073-4394-86c4-bdd510f661bf
ORCID for Raimund J. Ober: ORCID iD orcid.org/0000-0002-1290-7430

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Date deposited: 01 Mar 2019 17:30
Last modified: 20 Jul 2019 00:22

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Contributors

Author: Edward A.K. Cohen
Author: Anish V. Abraham
Author: Sreevidhya Ramakrishnan
Author: Raimund J. Ober ORCID iD

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