Imperial College London
Portrait Picture

Dr Ed Cohen

Faculty of Natural Sciences, Department of Mathematics

Reader in Statistics
 
 
 
//

Contact

 

+44 (0)20 7594 3986e.cohen

 
 
//

Location

 

536Huxley BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@article{Cohen:2019:10.1038/s41467-019-08689-x,
author = {Cohen, E and Abraham, A and Ramakrishnan, S and Ober, R},
doi = {10.1038/s41467-019-08689-x},
journal = {Nature Communications},
title = {Resolution limit of image analysis algorithms},
url = {http://dx.doi.org/10.1038/s41467-019-08689-x},
volume = {10},
year = {2019}
}
Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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.
AU  - Cohen,E
AU  - Abraham,A
AU  - Ramakrishnan,S
AU  - Ober,R
DO  - 10.1038/s41467-019-08689-x
PY  - 2019///
SN  - 2041-1723
TI  - Resolution limit of image analysis algorithms
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-019-08689-x
UR  - http://hdl.handle.net/10044/1/66988
VL  - 10
ER  -
Download