Evaluating the index of panoramic X-ray image quality using K-means clustering method
Abstract Background A panoramic X-ray image is generally considered optimal when the occlusal plane is slightly arched, presenting with a gentle curve. However, the ideal angle of the occlusal plane has not been determined. This study provides a simple evaluation index for panoramic X-ray image qual...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-01-01
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| Series: | The Egyptian Journal of Radiology and Nuclear Medicine |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s43055-023-01176-w |
| _version_ | 1827388693210464256 |
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| author | Satoshi Imajo Yoshinori Tanabe Nobue Nakamura Mitsugi Honda Masahiro Kuroda |
| author_facet | Satoshi Imajo Yoshinori Tanabe Nobue Nakamura Mitsugi Honda Masahiro Kuroda |
| author_sort | Satoshi Imajo |
| collection | DOAJ |
| description | Abstract Background A panoramic X-ray image is generally considered optimal when the occlusal plane is slightly arched, presenting with a gentle curve. However, the ideal angle of the occlusal plane has not been determined. This study provides a simple evaluation index for panoramic X-ray image quality, built using various image and cluster analyzes, which can be used as a training tool for radiological technologists and as a reference for image quality improvement. Results A reference panoramic X-ray image was acquired using a phantom with the Frankfurt plane positioned horizontally, centered in the middle, and frontal plane centered on the canine teeth. Other images with positioning errors were acquired with anteroposterior shifts, vertical rotations of the Frankfurt plane, and horizontal left/right rotations. The reference and positioning-error images were evaluated with the cross-correlation coefficients for the occlusal plane profile, left/right angle difference, peak signal-to-noise ratio (PSNR), and deformation vector fields (DVF). The results of the image analyzes were scored for positioning-error images using K-means clustering analysis. Next, we analyzed the correlations between the total score, cross-correlation analysis of the occlusal plane curves, left/right angle difference, PSNR, and DVF. In the scoring, the positioning-error images with the highest quality were the ones with posterior shifts of 1 mm. In the analysis of the correlations between each pair of results, the strongest correlations (r = 0.7–0.9) were between all combinations of PSNR, DVF, and total score. Conclusions The scoring of positioning-error images using K-means clustering analysis is a valid evaluation indicator of correct patient positioning for technologists in training. |
| first_indexed | 2024-03-08T16:22:35Z |
| format | Article |
| id | doaj.art-a57d1346e9794c08a71d9ed2cc995411 |
| institution | Directory Open Access Journal |
| issn | 2090-4762 |
| language | English |
| last_indexed | 2024-03-08T16:22:35Z |
| publishDate | 2024-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | The Egyptian Journal of Radiology and Nuclear Medicine |
| spelling | doaj.art-a57d1346e9794c08a71d9ed2cc9954112024-01-07T12:17:17ZengSpringerOpenThe Egyptian Journal of Radiology and Nuclear Medicine2090-47622024-01-015511810.1186/s43055-023-01176-wEvaluating the index of panoramic X-ray image quality using K-means clustering methodSatoshi Imajo0Yoshinori Tanabe1Nobue Nakamura2Mitsugi Honda3Masahiro Kuroda4Division of Radiology, Medical Support Department, Okayama University HospitalFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityDivision of Radiology, Medical Support Department, Okayama University HospitalDivision of Radiology, Medical Support Department, Okayama University HospitalFaculty of Medicine, Graduate School of Health Sciences, Okayama UniversityAbstract Background A panoramic X-ray image is generally considered optimal when the occlusal plane is slightly arched, presenting with a gentle curve. However, the ideal angle of the occlusal plane has not been determined. This study provides a simple evaluation index for panoramic X-ray image quality, built using various image and cluster analyzes, which can be used as a training tool for radiological technologists and as a reference for image quality improvement. Results A reference panoramic X-ray image was acquired using a phantom with the Frankfurt plane positioned horizontally, centered in the middle, and frontal plane centered on the canine teeth. Other images with positioning errors were acquired with anteroposterior shifts, vertical rotations of the Frankfurt plane, and horizontal left/right rotations. The reference and positioning-error images were evaluated with the cross-correlation coefficients for the occlusal plane profile, left/right angle difference, peak signal-to-noise ratio (PSNR), and deformation vector fields (DVF). The results of the image analyzes were scored for positioning-error images using K-means clustering analysis. Next, we analyzed the correlations between the total score, cross-correlation analysis of the occlusal plane curves, left/right angle difference, PSNR, and DVF. In the scoring, the positioning-error images with the highest quality were the ones with posterior shifts of 1 mm. In the analysis of the correlations between each pair of results, the strongest correlations (r = 0.7–0.9) were between all combinations of PSNR, DVF, and total score. Conclusions The scoring of positioning-error images using K-means clustering analysis is a valid evaluation indicator of correct patient positioning for technologists in training.https://doi.org/10.1186/s43055-023-01176-wQuality improvementSignal-to-noise ratioPanoramic X-ray imagesCluster analysisOcclusal plane |
| spellingShingle | Satoshi Imajo Yoshinori Tanabe Nobue Nakamura Mitsugi Honda Masahiro Kuroda Evaluating the index of panoramic X-ray image quality using K-means clustering method The Egyptian Journal of Radiology and Nuclear Medicine Quality improvement Signal-to-noise ratio Panoramic X-ray images Cluster analysis Occlusal plane |
| title | Evaluating the index of panoramic X-ray image quality using K-means clustering method |
| title_full | Evaluating the index of panoramic X-ray image quality using K-means clustering method |
| title_fullStr | Evaluating the index of panoramic X-ray image quality using K-means clustering method |
| title_full_unstemmed | Evaluating the index of panoramic X-ray image quality using K-means clustering method |
| title_short | Evaluating the index of panoramic X-ray image quality using K-means clustering method |
| title_sort | evaluating the index of panoramic x ray image quality using k means clustering method |
| topic | Quality improvement Signal-to-noise ratio Panoramic X-ray images Cluster analysis Occlusal plane |
| url | https://doi.org/10.1186/s43055-023-01176-w |
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