Perceptibility of defects in an aluminum test object: a comparison of the RVG-S and first generation VIXA systems with and without added niobium filtration.

Wakoh, Mamoru; Farman, Allan G.; Scarfe, William C.; Kelly, Michael S.; Kuroyanagi, K

doi:10.1259/dmfr.24.4.9161163

Cited by 12 publications

(4 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A test object with a minimum thickness of 7 mm and several holes or disks having steps ranging 10m to 50m are usually employed. This method is considered suitable for obtaining reproducible results in the perceptibility curve test 8,[10][11][12]14) .…”

Section: Introductionmentioning

confidence: 99%

Assessing the Image Quality of a CCD-Based Digital Intraoral Radiography System. Application of Perceptibility Curve Test.

Yuki

Kitagawa

Wakoh

et al. 2000

Bull. Tokyo Dent. Coll.

View full text Add to dashboard Cite

The perceptibility curve test is a method for evaluating the psychophysical properties of radiographic systems. The concept of the perceptibility curve is based on the minimum perceptible exposure differences that are recorded by a particular imaging system. The perceptibility curve test was applied to a Charge-Coupled Device (CCD)-based digital intraoral radiography system in this study. A test object was made of a square aluminum block, 28 mm in both height and length and 10 mm in thickness. The test object had ten contrast details in the form of round holes with diameters of 1.5 mm. The depths of the holes ranged from 0.05 mm to 0.5 mm in steps of 0.05 +/- 0.01 mm. An X-ray unit was used that operated in the range of 60 to 90 kVp. Test radiographs were shown to observers in random order. Six observers were asked to rate them regarding the number of spots representing holes that they could perceive. The smallest perceptible difference in gray level on the computer monitor, a 15-inch cathode-ray tube (CRT), was then found. The minimum difference in gray level between a perceptible detail and the background was determined. Dose response functions were employed to determine exposures corresponding to these gray levels. For each case, delta logE as a function of the number of object details was calculated. Finally the reciprocal of all values of (delta logE)min were calculated. The number of details which the observers perceived decreased linearly with decreasing delta logE values. The maximum number of details that observers perceived was eight or nine. The perceptibility curves showed that their peaks shifted slightly with a change of the kVp but that their shapes were similar at different kVp settings.

show abstract

Section: Introductionmentioning

confidence: 99%

Assessing the Image Quality of a CCD-Based Digital Intraoral Radiography System. Application of Perceptibility Curve Test.

Yuki

Kitagawa

Wakoh

et al. 2000

Bull. Tokyo Dent. Coll.

View full text Add to dashboard Cite

show abstract

“…While the authors concede the system MTF is not directly related to the clinical quality of the images they do recommend measurements of system resolution as a valid way to compare radiographic systems. Wakoh, et al (1995) used low contrast detectability as a means of comparison between two digital sensors. The impact of exposure and added filtration on the perception of defects in an aluminum test object were measured.…”

Section: Objective Image Quality Evaluationsmentioning

confidence: 99%

Image Optimization in Digital Dental Radiography

Silverstrim¹,

Schneider²,

Hoeven³

2015

Health Physics

View full text Add to dashboard Cite

When the United States Air Force completed a multi-million dollar transition to digital dental radiography in 2010 there was no quantitative method available for establishing the appropriate balance of image quality and radiation dose. The objective of this research was to devise a process to fill this need. Through computer simulation and clinical validation the effect of technical parameters on digital dental radiographic image quality was investigated and an optimization method was devised. The Monte Carlo NParticle Extended (MCNPX) radiation transport code was used to model the DC Planmeca Intra and AC Gendex 770 dental intraoral radiographic units and a unique anthropomorphic phantom simulating dental bitewing anatomy. The Carestream 6100 RVG sensor signal response, noise response, dose rate dependence and reproducibility were determined experimentally, as were their uncertainties and the inter-and intraradiographic unit variabilities. The experimental measurements were used to calibrate and scale the MCNPX generated data for the optimization analysis. The technical parameters modified in the simulation were peak kilovoltage, (50 through 90) and tube filtration (inherent, 0.1 mm and 0.2 mm added copper). The entrance air KERMA (~720 Gy) at the current clinical technique (63 kVp at 1 milliAmpere-seconds) was used to establish the reference image quality metrics for comparison. Four figures of merit (FOM) were chosen to encompass the impact of variations in the adjustable parameters.vii With equal weighting of all FOMs and given no limitations on the equipment, the optimal combination of kVp and tube filtration for dental bitewing imaging identified was 90 kVp with 0.1 mm added copper filtration. The optimal technique in the radiographic units' operating range was 70 kVp and 0.1 mm added copper filtration, which could be immediately adopted for a ~50% (+/-17%) entrance dose and ~40% effective dose savings (Planmeca units). In general, the optimization method facilitates image quality standardization across different radiographic units and sensors in a dental clinic. The unique computer model and optimization method used could be easily customized to evaluate any adult or pediatric intraoral imaging task. The results underscore the importance of tailoring the technical parameters to the particular imaging devices in service.viii Table of yet been achieved and it does not address digital dental radiography. However, the methods used for general radiology may serve as a guide.Several authors have reported techniques for image quality optimization. A number of these studies will be reviewed in an attempt to identify techniques that may be useful in digital dental imaging. Alternative approaches will also be explored.The dose versus image quality optimization process must be approached in several steps. First, a method must be identified to optimize the technical components of the imaging chain. That is, the appropriate radiographic technique for the chosen digital sensors must be determined with...

show abstract

“…Therefore, the PC test has been applied to evaluate and compare different digital intraoral systems without consideration of dentists' radiological experience. [2][3][4][5][6][7][8][9] The PC test has also been applied to evaluate the effect of different image enhancement modalities on perception. [10][11][12][13] In dentistry, there is a constant innovation of digital techniques.…”

Section: Introductionmentioning

confidence: 99%

Comparison of psychophysical properties of two intraoral digital sensors on low-contrast perceptibility

Shi

Benchimol²,

Näsström³

2013

Dentomaxillofacial Radiology

View full text Add to dashboard Cite

Objectives: The psychophysical properties of a new complementary metal oxide semiconductor-based detector, ProSensor ® (Planmeca Oy, Helsinki, Finland), in terms of dose response function and perceptibility curve test were performed and compared with those of a charged couple device-based sensor, Dixi ® (Planmeca Oy). Methods: Dose response functions at 66 kVp for a Dixi and a ProSensor were determined by means of multiple exposures to a homogeneous X-ray field covering the whole exposure range. The entry dose of each exposure was measured and registered. The mean grey level in each image was plotted as function of the corresponding exposures for both digital systems. Radiographs of a test object containing ten holes of increasing depth were obtained throughout the exposure range of the two digital sensors at 66 kVp. 12 observers were asked to register the number of perceptible holes in each radiograph. Based on the mean value of the observers' evaluation, the perceptibility curves were constructed, and the integral value under the perceptibility curves were compared between two intraoral sensors. Results: The results based on dose response function showed that the ProSensor was more sensitive than the Dixi sensor. Paired t-test showed that the minimal perceptible low-contrast details were significantly higher for the ProSensor than for the Dixi sensor (p , 0.001). The integrals below the two perceptibility curves were 33.4 and 69.2 for the Dixi and ProSensor, respectively. Conclusion: Applying the new ProSensor may be beneficial to patients owing to its reduced radiation dose and increased perception for low-contrast details in dentistry.

show abstract

Perceptibility of defects in an aluminum test object: a comparison of the RVG-S and first generation VIXA systems with and without added niobium filtration.

Abstract: The two systems performed equally at optimum exposure when the dose is approximately the same irrespective of the presence or absence of niobium filtration. Beyond the optimal level, the RVG-S outperformed the VIXA system.

Cited by 12 publications

References 17 publications

Assessing the Image Quality of a CCD-Based Digital Intraoral Radiography System. Application of Perceptibility Curve Test.

Assessing the Image Quality of a CCD-Based Digital Intraoral Radiography System. Application of Perceptibility Curve Test.

Image Optimization in Digital Dental Radiography

Comparison of psychophysical properties of two intraoral digital sensors on low-contrast perceptibility

Contact Info

Product

Resources

About