Image-Based Pore Space and Pore Network Characterization: A Review of 2D/3D Workflow in Foods.

Authors

Bobby Shekarau Luka, Abdul'alim Gambo Ibrahim, Ibrahim Binni Muhammed, Bello Mohammed Yunusa, Mohammed Haris Siddiqui, Khwaja Osama

Published in

Journal of food science. Volume 91. Issue 9. Pages e71450.

Abstract

Food microstructure plays an important role in governing mass transfer and textural properties during processing; hence, its characterization is essential for process optimization and product quality improvement. In this review, the application of image processing techniques for the characterization of pore spaces and pore networks in foods was examined. The workflow comprises image acquisition, preprocessing, segmentation, reconstruction, 2D/3D visualization, and quantitative analysis. Potentials and limitations of scanning electron microscopy (SEM) and X-ray micro-computed tomography (X-ray micro-CT) were elucidated. Published studies were analyzed to evaluate how image resolution, image quality, and segmentation methods influenced the results of pore space and pore network characterization. The reviewed literature showed that segmentation algorithms and imaging resolution are the two most critical factors influencing the accuracy of pore space and pore network characterization. SEM provides high-resolution surface information; X-ray micro-CT offers non-destructive 3D visualization of internal pore structures. This demonstrates an important trade-off between the two techniques. The relationship between image-based pore structure, food texture, and mass transfer processes in foods was elucidated. The state-of-the-art, challenges, emerging trends, and future research directions were identified and discussed. These include the lack of validation or benchmark datasets and the need for benchmark datasets and the need for a focus on AI-assisted/explainable/interpretable AI-based segmentation algorithms and multiscale imaging approaches. These developments will offer new opportunities for improving the accuracy and deployment of image-based pore characterization, thereby supporting the design of optimized food processing operations, improving texture prediction and mass transfer, and advancing quality control in food engineering.

PMID:
42720082
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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