ArticleGels (Basel, Switzerland)2025
PoreVision: A Program for Enhancing Efficiency and Accuracy in SEM Pore Analyses of Gels and Other Porous Materials.
Article in Gels (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- A low-cost imaging platform for quantitative characterisation of scaffold surface macrotopography with potential application in craniofacial tissue engineering.Medical & biological engineering & computing · 2026Article
- Data-driven multiscale design of composite biomaterials: Integrating experiments, imaging, and computational modeling for biomedical engineering.Materials today. Bio · 2026Review
- Keratin Additive for Cellular Adhesion in Transcutaneous Prosthetics.Journal of tissue engineering and regenerative medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Porous gels are frequently utilized as cell scaffolds in tissue engineering. Previous studies have highlighted the significance of scaffold pore size and pore orientation in influencing cell migration and differentiation. Moreover, there exists a considerable body of research focused on optimizing pore characteristics to enhance scaffold performance. However, current methods for numerical pore characterization typically involve expensive machines or manual size measurements using image manipulation software. In this project, our objective is to develop a user-friendly, versatile, and freely accessible software tool using Python scripting. This tool aims to streamline and objectify pore characterization, thereby accelerating research efforts and providing a standardized framework for researchers working with porous gels. Our group found that first-time users of PoreVision and ImageJ take similar amounts of time to use both programs; however, PoreVision is capable of handling larger datasets with reduced variability. Further, PoreVision users exhibited lower variability in area and orientation measurements compared to ImageJ, while perimeter variability was similar between the two. PoreVision showed higher variability in average measurements, likely due to its larger sample size and broader range of pore sizes, which may be missed in ImageJ's manual scanning approach. By facilitating quantitative analysis of pore size, shape, and orientation, our software tool will contribute to a more comprehensive understanding of scaffold properties and their impact on cellular behavior. Ultimately, we aim to aid researchers in the field of tissue engineering with a user-friendly tool that enhances the reproducibility and reliability of pore characterization analyses.
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Registered trials
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