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Automatic pore size measurements from scanning electron microscopy images of porous scaffolds

Lookup NU author(s): Dr Nilly Hojat, Dr Piergiorgio GentileORCiD, Dr Ana Ferreira-DuarteORCiD, Professor Lidija Siller



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


© 2022, Crown. Pore sizes and distribution are amongst the main morphological characteristics of porous scaffolds which indicate the suitability of scaffolds for many biological applications. Scaffolds usually have complex structures and are designed to have a specific range of pore sizes appropriate for target cells. Pore sizes are commonly estimated manually or based on semi-automatic techniques requiring high level of human intervention. Such methods are time consuming and subject to error, mainly due to lack of consistency in the process and subjective nature of the results following operator involvement. In this work, we present a novel image processing method for the measurement pore size distribution (the main morphological characteristics of scaffolds) independent from their complexity. We use thresholding, based on the histogram analysis, to segment pore areas from scaffold, followed by morphological filters to separate pores from each other. This algorithm provides robust detection and measurement of pore sizes and the distribution. The performance of the algorithm is assessed using standard calibration kit which is used for calibration of Scanning Electron Microscopy (SEM) imaging systems. The results showed consistent output with 1.3% average error as compared against their true size. The algorithm was applied to 3D Apatite-Wollastonite scaffolds manufactured using the Thermally Induced Phase Separation technique. The results were robust and consistent with visual evaluation of SEM images. The algorithm also provides the morphology of each pore and, subsequently, offering further comprehension of the influence of microstructures across a range of fields, such as tissue engineering processes.

Publication metadata

Author(s): Hojat N, Gentile P, Ferreira AM, Siller L

Publication type: Article

Publication status: Published

Journal: Journal of Porous Materials

Year: 2023

Volume: 30

Pages: 93-101

Print publication date: 01/02/2023

Online publication date: 11/08/2022

Acceptance date: 12/07/2022

Date deposited: 11/07/2022

ISSN (print): 1380-2224

ISSN (electronic): 1573-4854

Publisher: Springer Nature


DOI: 10.1007/s10934-022-01309-y


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Funder referenceFunder name
Arthritis Research UK
Glass Technology Services Ltd
VERSUS Arthritis