The impact of digital image processing artefacts mimicking pathological features associated with restorations

A blurring correction method suitable to analyze quantitative x-ray images derived from energy-resolving photon counting detector

Objective.The purpose of this study is to propose a novel blurring correction method that enables accurate quantitative analysis of the object edge when using energy-resolving photon counting detectors (ERPCDs). Although the ERPCDs have the ability to generate various quantitative analysis techniques, such as the derivations of effective atomic number (Zeff) and bone mineral density values, at the object edge in these quantitative images, accurate quantitative information cannot be obtained. This is because image blurring prevents the gathering of accurate primary x-ray attenuation information.Approach.We developed the following procedure for blurring correction. A 5 × 5 pixels masking region was set as the processing area, and the pixels affected by blurring were extracted from the analysis of pixel value distribution. The blurred pixel values were then corrected to the proper values estimated by analyzing minimum and/or maximum values in the set mask area. The suitability of our correction method was verified by a simulation study and an experiment using a prototype ERPCD.Main results. WhenZeffimage of aluminum objects (Zeff= 13) were analyzed without applying our correction method, regardless of raw data or correction data applying a conventional edge enhancement method, the properZeffvalues could not be derived for the object edge. In contrast, when applying our correction method, 82% of pixels affected by blurring were corrected and the properZeffvalues were calculated for those pixels. As a result of investigating the applicability limits of our method through simulation, it was proven that it works effectively for objects with 4 × 4 pixels or more.Significance. Our method is effective in correcting image blurring when the quantitative image is calculated based on multiple images. It will become an in-demand technology for putting a quantitative diagnosis into actual medical examinations.

Impact of enhancement filters of a CMOS system on halo artifact expression at the bone-to-implant interface

OBJECTIVE

To assess the impact of enhancement filters on the formation of halo artifacts in radiographs of dental implants obtained with a complementary metal oxide semiconductor (CMOS) system.

METHODS

Digital radiographs of dental implants placed in dry human mandibles were processed with the Noise Reduction smoothing filter, as well as the Sharpen 1, Sharpen 4, and Sharpen UM high-pass filters available in the CLINIVIEW™ software (Instrumentarium Dental, Tuusula, Finland). Subjective analysis involved evaluating the left, right, and apical surfaces of each implant for the presence of much, few, or no halo. The objective analysis involved measurement of the halo area using the Trainable Weka Segmentation plugin (ImageJ, National Institutes of Health, Bethesda, MD, USA). Data were analyzed using Friedman's test (subjective analysis) and ANOVA (objective analysis) (α = 5%).

RESULTS

In the subjective evaluation, the Sharpen 4 filter produced more radiographs with much halo present, and in the objective evaluation, a bigger halo area when compared to the original images and the Noise Reduction filter for all surfaces (p < 0.05).

CONCLUSIONS

When evaluating dental implants, priority should be given to original images and those enhanced with smoothing filters since they exhibit fewer halo artifacts.

CLINICAL RELEVANCE

Post-processing tools, such as enhancement filters, may improve the image quality and assist some diagnostic tasks. However, little is known regarding the impact of enhancement filters in halo formation on CMOS systems, which have been increasingly used in dental offices.

Automatic detection of image sharpening in maxillofacial radiology

BACKGROUND

Improvement of image quality in radiology, including the maxillofacial region, is important for diagnosis by enhancing the visual perception of the original image. One of the most used modification methods is sharpening, in which simultaneously with the improvement, due to edge enhancement, several artifacts appear. These might lead to misdiagnosis and, as a consequence, to improper treatment. The purpose of this study was to prove the feasibility and effectiveness of automatic sharpening detection based on neural networks.

METHODS

The in-house created dataset contained 4290 X-ray slices from different datasets of cone beam computed tomography images were taken on 2 different devices: Ortophos 3D SL (Sirona Dental Systems GmbH, Bensheim, Germany) and Planmeca ProMax 3D (Planmeca, Helsinki, Finland). The selected slices were modified using the sharpening filter available in the software RadiAnt Dicom Viewer software (Medixant, Poland), version 5.5. The neural network known as "ResNet-50" was used, which has been previously trained on the ImageNet dataset. The input images and their corresponding sharpening maps were used to train the network. For the implementation, Keras with Tensorflow backend was used. The model was trained using NVIDIA GeForce GTX 1080 Ti GPU. Receiver Operating Characteristic (ROC) analysis was performed to calculate the detection accuracy using MedCalc Statistical Software version 14.8.1 (MedCalc Software Ltd, Ostend, Belgium). The study was approved by the Ethical Committee.

RESULTS

For the test, 1200 different images with the filter and without modification were used. An analysis of the detection of three different levels of sharpening (1, 2, 3) showed sensitivity of 53%, 93.33%, 93% and specificity of 72.33%, 84%, 85.33%, respectively with an accuracy of 62.17%, 88.67% and 89% (p < 0.0001). The ROC analysis in all tests showed an Area Under Curve (AUC) different from 0.5 (null hypothesis).

CONCLUSIONS

This study showed a high performance in automatic sharpening detection of radiological images based on neural network technology. Further investigation of these capabilities, including their application to different types of radiological images, will significantly improve the level of diagnosis and appropriate treatment.

Misfit detection in implant-supported prostheses of different compositions by periapical radiography and cone beam computed tomography: An in vitro study

STATEMENT OF PROBLEM

Misfits at the implant-abutment joint (IAJ) can cause the biological and mechanical failure of implant therapy. Standard parallel periapical radiography (PERI) is the method of choice for assessing the fitting of implant-supported prostheses. Although current guidelines do not support the use of cone beam computed tomography (CBCT) solely for misfit detection, CBCT scans can also register misfits as imaging findings. Whether the material used for prostheses manufacturing influences misfit appearance in PERI and CBCT images is unknown.

PURPOSE

The purpose of this in vitro study was to assess the influence of the type of prosthesis material on misfit detection at the IAJ by using PERI and CBCT.

MATERIAL AND METHODS

Thirty-two implants with an external hexagon connection were placed in dried human mandibles. Implant-supported crowns were manufactured with different materials and allocated to 3 experimental groups: metal-ceramic (MC), titanium abutment veneered with acrylic resin (TIT), and zirconia abutment veneered with glass-ceramic (ZIR). All crowns were installed both with and without a simulated 200-μm-thick gap at the IAJ (n=64) and were assessed by PERI and CBCT scans. Four dentists evaluated the images for the presence or absence of misfit. Statistical analysis included the Kappa test and areas under the receiver operating characteristics curve (Az values) comparisons (α=.05).

RESULTS

Kappa values indicated almost perfect intraevaluator and interevaluator reproducibility for PERI and ranged from fair to almost perfect for CBCT. For PERI, Az values were not significantly different among the MC (0.995), TIT (0.997), and ZIR groups (1.000) (P>.05). Regarding CBCT, the Az values found for TIT (0.941) and MC (0.890) were significantly higher than for ZIR (0.762) (P<.05). Az values for PERI were significantly higher than for CBCT (P<.05).

CONCLUSIONS

The type of prosthesis material did not influence misfit detection at the IAJ with PERI; however, ZIR had lower diagnostic accuracy than TIT and MC implant-supported crowns with CBCT.

Postprocessing of all-zirconia restorations in digital dental radiographs: a quality assurance predicament

OBJECTIVES

The aim of this study was to describe a quality assurance issue, that is, the production of nondiagnostic high-contrast radiographs when imaging teeth restored with all-zirconia crowns on bitewing radiographs.

STUDY DESIGN

All-zirconia crowns were imaged with DIGORA Optime photostimulable phosphor (PSP) plates (Soredex/Orion Corp., Helsinki, Finland). To assess the differences in software processing, the PSP plates were scanned into third-party software as well as directly into the twain and native software provided by the manufacturer. Gamma correction, histogram stretch, and scanner resolution settings were adjusted. Vertical bitewings were acquired to increase anatomic coverage.

RESULTS

Scanning into third-party software or directly into the twain and native software did not improve contrast. Shifting the lower limit of the histogram stretch to 3 with a gamma correction of 2 resolved the problem. Neither scanner resolution setting nor vertical bitewings improved contrast.

CONCLUSIONS

The nondiagnostic high-contrast radiographs result from imaging software not effectively displaying the available gray scale. The software processing error appears to be initiated by the high-attenuation characteristics of zirconia. Consequently, radiographs with a high ratio of zirconia crown to normal anatomy are particularly susceptible.

Is Panoramic Radiography an Accurate Imaging Technique for the Detection of Endodontically Treated Asymptomatic Apical Periodontitis?

INTRODUCTION

This study aimed to evaluate the diagnostic accuracy of panoramic radiography (PAN) for the detection of clinically/surgically confirmed apical periodontitis (AP) in root canal-treated teeth using cone-beam computed tomographic (CBCT) imaging as the reference standard.

METHODS

Two hundred forty patients with endodontically treated AP (diseased group) were detected via CBCT imaging using the periapical index system. They were divided into groups of 20 each according to lesion size (2-4.5 mm and 4.6-7 mm) and anatomic area (incisor, canine/premolar, and molar) in both the upper and lower arches. Another 240 patients with root filling and a healthy periapex (healthy group) were selected. All diseased and healthy patients underwent PAN first and a CBCT scan within 40 days. The periapical index system was also used to assess AP using PAN. Sensitivity, specificity, diagnostic accuracy, positive predictive value, and negative predictive value for PAN images with respect to CBCT imaging were analyzed. The k value was calculated to assess both the interobserver reliability for PAN and the agreement between PAN and CBCT.

RESULTS

PAN showed low sensitivity (48.8), mediocre negative predictive value (64.7), good diagnostic accuracy (71.3), and high positive predictive value (88.6) and specificity (93.8). Both interobserver reliability for PAN and agreement between PAN and CBCT were moderate (k = 0.58 and 0.42, respectively). The best identified AP was located in the lower canine/premolar and molar areas, whereas the worst identified AP was located in the upper/lower incisor area and upper molar area.

CONCLUSIONS

PAN showed good diagnostic accuracy, high specificity, and low sensitivity for the detection of endodontically treated AP.

Medical physics 3.0 versus 1.0: A case study in digital radiography quality control

PURPOSE

The study illustrates how a renewed approach to medical physics, Medical Physics 3.0 (MP3.0), can identify performance decrement of digital radiography (DR) systems when conventional Medical Physics 1.0 (MP1.0) methods fail.

METHODS

MP1.0 tests included traditional annual tests plus the manufacturer's automated Quality Assurance Procedures (QAP) of a DR system before and after a radiologist's image quality (IQ) complaint repeated after service intervention. Further analysis was conducted using nontraditional MP3.0 tests including longitudinal review of QAP results from a 15-yr database, exposure-dependent signal-to-noise (SNR² ), clinical IQ, and correlation with the institutional service database. Clinical images were analyzed in terms of IQ metrics by the Duke University Clinical Imaging Physics Group using previously validated software.

RESULTS

Traditional metrics did not indicate discrepant system performance at any time. QAP reported a decrease in contrast-to-noise ratio (CNR) after detector replacement, but remained above the manufacturer's action limit. Clinical images showed increased lung noise (Ln), mediastinum noise (Mn), and subdiaphragm-lung contrast (SLc), and decreased lung gray level (Lgl) following detector replacement. After detector recalibration, QAP CNR improved, but did not return to previous levels. Lgl and SLc no longer significantly differed from before detector recalibration; however, Ln and Mn remained significantly different. Exposure-dependent SNR² documented the detector operating within acceptable limits 9 yr previously but subsequently becoming miscalibrated sometime before four prior annual tests. Service records revealed catastrophic failure of the computer containing the original detector calibration from 11 yr prior. It is likely that the incorrect calibration backup file was uploaded at that time.

CONCLUSIONS

MP1.0 tests failed to detect substandard system performance, but MP3.0 methods determined the root cause of the problem. MP3.0 exploits the wealth of data with more sensitive performance indicators. Data analytics are powerful tools whose proper application could facilitate early intervention in degraded system performance.

Imaging evaluating of the implant/bone interface-an in vitro radiographic study

OBJECTIVES

To analyze the diagnostic accuracy of conventional and digital radiographic images and the impact of digital filters in evaluating the bone-implant interface.

METHODS

Titanium implants were inserted into 74 fresh bovine ribs blocks, 37 fitting tight to the bone walls (simulating the existence of osseointegration) and 37 with a gap of 0.125 mm (simulating a failure in the osseointegration process). Periapical radiographs were taken with conventional film and two phosphor plate systems [VistaScan^® (Dürr Dental, Bietigheim-Bissingen, Germany) and Express^® (Instrumentarium, Tuusula, Finland)]. Digital radiographs were investigated with and without enhancement filters. Three blinded examiners assessed the images for the presence of juxtaposition in the bone-implant interface using a five-point Likert scale. Sensitivity, specificity and the area under the receiver-operating characteristic curve (AUC) and its 95% confidence interval (CI) were calculated for each variable. Intraexaminer and interexaminer agreements were analyzed using Kendall's concordance test.

RESULTS

Intraexaminer and interexaminer agreements were >0.80 for both digital and conventional images. Conventional radiographs (AUC = 0.963/CI = 0.891 to 0.993) and digital images with high enhancement filters such as Caries2 (AUC = 0.964/CI = 0.892 to 0.993), Endo (AUC = 0.952/CI = 0.875 to 0.988) and Sharpen3 (AUC = 0.894/CI = 0.801 to 0.954) showed the greatest accuracy for evaluating the bone-implant interface. Original images from both digital systems and the further enhancement filters tested showed low sensitivity for the diagnosis task tested.

CONCLUSIONS

Conventional radiographs or digital radiographs with high-pass filters could help enhance diagnosis on implant-bone interface.

Evaluation of low-contrast perceptibility in dental restorative materials under the influence of ambient light conditions

OBJECTIVES

This study aimed to assess how details on dental restorative composites with different radio-opacities are perceived under the influence of ambient light.

METHODS

Resin composite step wedges (six steps, each 1-mm thick) were custom manufactured from three materials, respectively: (M1) Filtek™ Z350 (3M/ESPE, Saint Paul, MN); (M2) Prisma AP.H™ (Dentsply International Inc., Brazil) and (M3) Glacier(®) (SDI Limited, Victoria, Australia). Each step of the manufactured wedge received three standardized drillings of different diameters and depths. An aluminium (Al) step wedge with 12 steps (1-mm thick) was used as an internal standard to calculate the radio-opacity as pixel intensity values. Standardized digital images of the set were obtained, and 11 observers independently recorded the images, noting the number of noticeable details (drillings) under 2 dissimilar conditions: in a light environment (light was turned on in the room) and in low-light conditions (light in the room was turned off). The differences between images in terms of the number of details that were observed were statistically compared using ANOVA, Cronbach's alpha coefficient and Wilcoxon and Kruskal-Wallis tests, with a significance level setting of 5% (α = 0.05).

RESULTS

The M2 showed higher radio-opacity, the M1 displayed intermediate radio-opacity and the M3 showed lower radio-opacity, respectively; however, all three were without significance (p > 0.05) compared with each other. The differences in radio-opacity resulted in a significant variation (p < 0.05) in the number of noticeable details in the image, which were influenced by characteristics of details, in addition to the ambient-light level.

CONCLUSIONS

The radio-opacity of materials and ambient light can affect the perception of details in digital radiographic images.