Evaluation of Virtual Grid Processed Clinical Chest Radiographs.
Invest Radiol
; 57(9): 585-591, 2022 09 01.
Article
de En
| MEDLINE
| ID: mdl-35438670
ABSTRACT
OBJECTIVES:
We evaluated the different Virtual Grid software ratios (Fujifilm, Tokyo, Japan) on gridless clinical chest radiographs with visual grading analysis (VGA). In addition, we investigated the 2 image quality assessment algorithms (IQAAs). MATERIALS ANDMETHODS:
Gridless chest radiographs of 50 different intensive care unit patients were collected and afterward processed with Virtual Grid software. Different software (SW) grid ratios-61, 101, 131, 171, and 201-were applied to investigate the image quality (IQ) improvement. Image quality improvement was assessed by 4 radiologists in a relative VGA study where the reference image was processed with SW grid ratio of 101. One of the IQAAs used to analyze the radiographs was implemented in our department but was originally developed by the research group of the Duke University Medical Center. A general IQ score (IQS) was calculated based on contrast, detail, and noise. Another IQAA-NIQE (naturalness image quality evaluator)-available in Matlab (MATLAB Research R2019b; the MathWorks, Inc) was evaluated. Both methods were compared with VGA.RESULTS:
Visual grading analysis scores of gridless radiographs are significantly lower ( P < 0.001). Image quality increases with increasing SW grid ratios, up to grid ratio of 171. However, some anatomical structures-spine and ribs-are negatively affected by the higher grid ratios. A correlation coefficient of 0.99 between the VGA and the IQS was observed. The correlation coefficient between VGA and NIQE was 1.00.CONCLUSIONS:
Virtual Grid with SW grid ratio of 61 improves the IQ of gridless chest bedside radiographs. The grid ratios 171 and 201 should be considered carefully as the SW negatively affects parts of the ribs and spine. Therefore, grid ratios up to 131 can be advised. The IQAAs are promising and could be used to detect differences in IQ when different scatter correction SW settings are used.
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Radiographie thoracique
/
Amélioration d'image radiographique
Type d'étude:
Diagnostic_studies
Limites:
Humans
Pays/Région comme sujet:
Asia
Langue:
En
Journal:
Invest Radiol
Année:
2022
Type de document:
Article