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. 2025 Jun;38(3):1812-1819.
doi: 10.1007/s10278-024-01298-1. Epub 2024 Oct 18.

The Application of ImageJ Software for Roughness Analysis of Dental Implants

Giovanna Nascimento Mendes  1 , Lara Góis Floresta  2 , Wilton Mitsunari Takeshita  3 , Bernardo Ferreira Brasileiro  4   5 , Cleverson Luciano Trento  4
Affiliations

The Application of ImageJ Software for Roughness Analysis of Dental Implants

Giovanna Nascimento Mendes et al. J Imaging Inform Med. 2025 Jun.

Abstract

ImageJ software is a versatile, open-source software for visualizing, processing, and analyzing images, which has contributed to its widespread adoption in the scientific community. A notable application of this software is its integration with scanning electron microscope images, where surface roughness can be quantified. This study aims to highlight the need for knowledge and standardization of the technique selected for analysis to ensure the viability of ImageJ software as a reliable alternative for evaluating the surface roughness of dental implants. Images obtained by scanning electron microscopy, depending on the plugin used or the researcher's standardization, yielded different surface roughness values, which were assessed via ImageJ. Thirty grade 4 titanium osseointegrated dental implants via all treated with similar surface treatment methods were studied. Two groups were formed for analysis via ImageJ: Group 1 assessed surface roughness using only the SurfCharJ plugin (n = 12), and Group 2 assessed surface roughness using both the roughness/waviness and SurfCharJ plugin (n = 18). The results showed that the use of different plugins can lead to different outcomes, potentially affecting the quality of the study. This study concluded that a standardized methodology is necessary to ensure consistency in results obtained via ImageJ.

Keywords: Dental implants; Digital profilometry; ImageJ software; Roughness; Scanning electron microscopy; Surface properties.

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Conflict of interest statement

Declarations. Competing Interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
3D reproduction (Surface Plot) of Group 1 samples. a Sample 1 neck region (500 ×). b Sample 2 neck region (500 ×). c Sample 3 neck region (500 ×). d Sample 4 neck region (500 ×). e Sample 5 neck region (500 ×) [10]. Accessibility: Figure of the surface topography. The image shows peaks and valleys in blue, purple, red, orange, and yellow indicating their elevation and depression on a micrometric scale
Fig. 2
Fig. 2
Three-dimensional reproduction of the surface waviness of Group 2 samples (interactive 3D). a Sample 1 neck region (4000 ×). b Sample 2 neck region (4000 ×). c Sample 3 neck region (4000 ×). d Sample 4 neck region (4000 ×). e Sample 5 neck region (4000 ×). Accessibility: Figure of the surface topography. The image depicts colored peaks and valleys showing their elevation and depression on a microscale (yellow, orange, and purple)
Fig. 3
Fig. 3
Three-dimensional reproduction of the surface roughness of Group 2 samples (interactive 3D). a Sample 1 neck region (4000 ×). b Sample 2 neck region (4000 ×). c Sample 3 neck region (4000 ×). d Sample 4 neck region (4000 ×). e Sample 5 neck region (4000 ×). Accessibility: Figure of the surface topography. The image depicts colored peaks and valleys, showing their elevation and depression on a micrometrical scale (purple and red colors)
Fig. 4
Fig. 4
Screenshot of the software ImageJ v1.49 (author’s gallery). Accessibility: Figure of the surface for SEM. The image depicts black and white peaks and valleys showing their elevation and depression on a micrometrical scale (purple, orange and red colors)
Graph 1
Graph 1
Descriptive analysis of Ra values of Group 1 with analyses 1 and 2. Paired t test for the same sample comparing the analyses yielded p < 0.001 for both Rq and Ra
Graph 2
Graph 2
Descriptive analysis of Ra values of Group 2 with analyses 1 and 2. Paired t test for the same sample comparing the analyses yielded p < 0.001 for both Rq and Ra
See this image and copyright information in PMC

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