Influence Of Voxel Size Research Articles

Porosity prediction in laser-based powder bed fusion of polyamide 12 using infrared thermography and machine learning

Achieving precise control in laser-based powder bed fusion of polymers is crucial for ensuring the structural integrity of aerospace and automotive components. Closed-loop feedback control systems using process monitoring techniques, such as infrared thermography, have the potential to provide reliable production by controlling the temperature of the melt. However, challenges arise from complex interactions among variables, such as part geometry, scan strategy, and laser parameters, affecting the melted polymer's temperatures and subsequent particle fusion. Thus, the correlation between thermal signals and resulting part density still needs to be clarified. In this work, a machine learning algorithm is trained to predict local porosity or, rather, solidity based on thermal and temporal features extracted from the melt's temperature-time profile. This enables statistical techniques to assess the contribution of the melt's thermal and temporal features in the decision-making process for evaluating porosity, along with the influence of voxel size and configuration. The in-situ process signature is measured using infrared thermography, and the porosity is analyzed by X-ray micro-computed tomography. The 2D thermal data is first converted into voxel information and then stitched with the 3D mircoCT data in a second step. The resulting 3D thermal features and porosity matrices are downsampled and utilized to train a machine learning algorithm (lightGBM). Models with high prediction accuracy are achieved using a small voxel size to avoid over-homogenizing features and by utilizing thermal signals from adjacent voxels to determine porosity in a volume element. The highest predictor for resulting porosity is the peak temperature of the melt during laser exposure. Interlayer effects, such as sufficient reheating of subsurface layers, are the second-highest indicator for dense parts. Furthermore, the model's performance is also affected by intra-layer effects, including the peak temperature of adjacent voxels and the cooling behavior after laser exposure. This research has several implications for industry, as it enables the detection of process defects based on in-situ process monitoring data without post-process material testing. Moreover, identifying thermal signal ranges that lead to the highest porosity can reduce the number of experiments needed for material qualification processes.

BrainAGE methods: influence of field strength, voxel size, race, and ethnicity

AbstractBackgroundThe brain‐age algorithm utilizes a regression model of the typical aging trajectory, trained on structural MRIs and chronological ages of a large population of healthy individuals spanning a wide age range (Cole et al. 2017, Neuroimage). MRIs from new populations are then compared to this regression for estimating brain age, a biomarker of brain health. Few studies have investigated stability of the brain‐age model across field strength and the influence of voxel size and race is understudied.MethodWe analyzed stability of the brain‐age model within and across field strength in the ADNI cohort (n = 75: 25 CN/25 MCI/25 AD) using intra‐class correlation coefficients (ICC) and multiple R2 values. Impact of voxel size (0.8mm, 1mm, and ADNI2 sequence 1.1×1.1×1.2mm) was compared in a sample from the Indiana ADRC (n = 48: 19 CN/16 SCD/10 MCI/3 AD). We then calculated brain age gap (BAG; estimated– chronological age) and compared results across self‐reported racial and ethnic groups matched on diagnosis, sex, age, education, and handedness using independent t‐tests. BAG results of African Americans (AAs) from the IADRC (n = 71: 30 CN/19 SCD/15 MCI/7 AD) and ADNI (n = 147: 41 CN/20 EMCI/27 LMCI/15 AD/44 SMC), and Hispanics (n = 76: 24 CN/16 EMCI/11 LMCI/11 AD/14 SMC) and Asians (n = 47: 12 CN/7 EMCI/4 LMCI/9 AD/15 SMC) from ADNI only, were compared to matched non‐Hispanic Whites (NHWs).ResultThe brain‐age method was stable across repeated scans within field strength, but less stable across field strengths (Fig.1). 3T scans consistently estimated individuals to be ∼4.43 years younger than the 1.5T scans. The method was relatively stable within and across voxel sizes (Fig.2). There was a significant difference in BAG between races (NHWs and AAs, and NHWs and Asians), but not between ethnicities (NHWs and Hispanics) (Fig.3).ConclusionDue to the model’s variability across field strength, we propose a linear offset equation for data harmonization (Fig.1): ((3T estimate/0.92)+9.55). We are also investigating ComBat harmonization to eliminate effects of field strength. While other studies show structural differences across race, it will be important to determine whether the self‐reported racial differences in BAG are due to inherent model bias or true biological differences.

BrainAGE methods: influence of field strength, voxel size, race, and ethnicity

AbstractBackgroundThe brain‐age algorithm utilizes a regression model of the typical aging trajectory, trained on structural MRIs and chronological ages of a large population of healthy individuals spanning a wide age range (Cole et al. 2017, Neuroimage). MRIs from new populations are then compared to this regression for estimating brain age, a biomarker of brain health. Few studies have investigated stability of the brain‐age model across field strength and the influence of voxel size and race is understudied.MethodWe analyzed stability of the brain‐age model within and across field strength in the ADNI cohort (n = 75: 25 CN/25 MCI/25 AD) using intra‐class correlation coefficients (ICC) and multiple R2 values. Impact of voxel size (0.8mm, 1mm, and ADNI2 sequence 1.1×1.1×1.2mm) was compared in a sample from the Indiana ADRC (n = 48: 19 CN/16 SCD/10 MCI/3 AD). We then calculated brain age gap (BAG; estimated– chronological age) and compared results across self‐reported racial and ethnic groups matched on diagnosis, sex, age, education, and handedness using independent t‐tests. BAG results of African Americans (AAs) from the IADRC (n = 71: 30 CN/19 SCD/15 MCI/7 AD) and ADNI (n = 147: 41 CN/20 EMCI/27 LMCI/15 AD/44 SMC), and Hispanics (n = 76: 24 CN/16 EMCI/11 LMCI/11 AD/14 SMC) and Asians (n = 47: 12 CN/7 EMCI/4 LMCI/9 AD/15 SMC) from ADNI only, were compared to matched non‐Hispanic Whites (NHWs).ResultThe brain‐age method was stable across repeated scans within field strength, but less stable across field strengths (Fig.1). 3T scans consistently estimated individuals to be ∼4.43 years younger than the 1.5T scans. The method was relatively stable within and across voxel sizes (Fig.2). There was a significant difference in BAG between races (NHWs and AAs, and NHWs and Asians), but not between ethnicities (NHWs and Hispanics) (Fig.3).ConclusionDue to the model’s variability across field strength, we propose a linear offset equation for data harmonization (Fig.1): ((3T estimate/0.92)+9.55). We are also investigating ComBat harmonization to eliminate effects of field strength. While other studies show structural differences across race, it will be important to determine whether the self‐reported racial differences in BAG are due to inherent model bias or true biological differences.

Influence of voxel size and filter type on detecting vertical root fracture using cone-beam computed tomography.

Vertical root fractures (VRFs) can start at any level of the root and progress longitudinally to the coronal attachment. This study aimed to investigate the effects of different exposure parameters used when obtaining CBCT scans in detecting simulated VRFs. Hence, 80 intact human mandibular single-rooted pre-molar teeth without root fractures were included in the study. No statistically significant difference was found between the filters in terms of VRF detection in the group with the roots with only root canal filling (Groups 1 and 5); however, 100 voxels were found to be more successful in terms of VRF detection than other voxel sizes. Results of this study suggest that using lower voxel sizes leads to an accurate diagnosis of vertical root fracture, in addition, our results revealed that using AR filters did not improve the diagnostic accuracy in detecting VRFs.

Influence of Voxel Size on Evaluation of Trabecular Bone Microstructure on Human Mandibles: A CBCT study

Purpose: This study aims to assess the effect of voxel size on trabecular microstructural evaluation onhuman cadaver mandiblesusing cone beam computed tomography (CBCT) images.
 Methods: Twenty two Volumes of Interest were obtained from to human cadaver mandibles which were scanned in three different voxel sizes using CBCT. Scanning performed in 0.125 mm (Group 1), 0.2 mm (Group 2) and 0.3 mm (Group 3) voxel sizes. Regions of interest are calculated in both mandibles for both voxel sizes which are adjusted from apical third of all interdental alveolar trabecular bone from anterior and posterior mandible. Trabecular thickness (Tb. Th); trabecular separation (Tb. Sp); Bone Volume/Total Volume (BV/TV) values were obtained using plug in BoneJ of the software ImageJ. The results were evaluated statistically in software IBM SPSS Statistics 21. 
 Results: Trabecular thickness and trabecular separation showed significant difference between first and the third and the second and the third groups (p=0.000), while first and second group did not. BV/TV values showed no significant difference between whole groups. 
 Conclusion: Beside microstructural analysis is not their first purpose CBCT images carry knowledge about trabecular bone microstructure could be a valuable bone quality assessment tool. High correlation between values with 0.125 mm and 0.2 mm and low correlation between values with 0.125 mm and 0.3 mm voxel sizes suggest that; this knowledge is clinically more valuable when voxel size is 0.2 mm or thinner.

Influence of voxel size on dentinal microcrack detection by micro-CT after root canal preparation.

The aim of this study was to assess the influence of micro-computed tomography (micro-CT) voxel size on dentinal microcrack detection after root canal preparation using rotary heat-treated nickel-titanium files. Curved mesial root canals (n = 24) of mandibular molars were prepared using ProDesign Logic 30/.05 (PDL) or HyFlex EDM 25/.08 (HEDM). The specimens were scanned by micro-CT at 5 μm voxel size before and after root canal preparation. The percentage of microcracks was evaluated in images at 5, 10 and 20 μm voxel size, by two examiners at two moments. The Kappa and McNemar tests (α = 0.05) were used. The percentage of dentinal microcracks was similar before and after PDL and HEDM preparations, at 10 and 20 μm (p > 0.05). HEDM showed a higher percentage of dentinal microcracks in the middle third at 5 μm after preparation (p < 0.05). The detection of dentinal microcracks before and after instrumentation using PDL was more accurate at 5 μm than at 20 μm, in all thirds (p < 0.05). Within the limitations of this ex vivo study, as expected, the results showed that different resolutions influence the micro-CT analysis of microcracks. The highest accuracy in detecting microcracks was observed for analyses performed at 5 μm voxel size. HyFlex EDM caused even more microcracks to develop in the middle third, detectable only by visualization of images made at 5 μm voxel size.

Influence of voxel size on micro-CT analysis of debris after root canal preparation.

The aim of this study was to assess the influence of micro-computed tomography (micro-CT) voxel size on the evaluation of debris accumulation after passive ultrasonic irrigation (PUI) in curved root canals prepared with rotary nickel-titanium files. Mesial root canals (n = 24) of mandibular molars with curvature between 25° and 35° were prepared using ProDesign Logic 30/.05 (PDL) or HyFlex EDM 25/.08 (HEDM). PUI was performed after root canal preparation of all root canals. The specimens were scanned using high-resolution (5 μm voxel size) micro-CT imaging before and after experimental procedures. The percentage of debris was analyzed in the middle and apical thirds using images with 5, 10 and 20 μm voxel sizes. Data were compared using unpaired and paired Student's t-test, ANOVA and Tukey's statistical tests (α = 0.05). There were no differences among the debris analyses performed at different voxel sizes (5, 10 and 20 μm) (p > 0.05). The percentage of debris was similar between the root canals prepared by PDL and HEDM before and after PUI (p > 0.05). In both groups, the percentage of debris decreased in the middle third after PUI (p < 0.05). Within the limitations of this ex vivo study, it can be concluded that the voxel sizes evaluated did not have a significant impact on the analysis of accumulated debris. However, the results showed a tendency for detection of more debris in the analysis performed using a lower voxel size. PUI decreased the debris accumulation in the middle third of curved root canals.

Influence of voxel size and point cloud density on crown cover estimation in poplar plantations using terrestrial laser scanning

Accurate estimates of crown cover (CC) are central for a wide range of forestry studies. As direct measurements do not exist to retrieve this variable in the field, CC is conventionally determined from optical measurements as the complement of gap fraction close to the zenith. As an alternative to passive optical measurements, active sensors like Light Detection and Ranging (LiDAR) allows for characterizing in situ the 3D canopy structure with unprecedented detail. We evaluated the reliability of terrestrial laser scanning (TLS) to estimate CC using a voxel-based approach. Specifically, we tested how different voxel sizes (5-20 cm) and voxel densities (1-9 points/dm 3 ) influenced the retrieval of CC. Results were compared against benchmark values obtained from DCP. The trial was performed in hybrid poplar plantations in Northern Italy. Results indicate that TLS can be used for obtaining accurate estimates of CC, but the choice of voxel size and point density is critical for achieving such accuracy. in hybrid poplars, the best performance was obtained using voxel size of 10 cm and point density of 8 points/dm 3 . The combined ability of measuring and mapping CC also holds great potential to use TLS for calibrating and upscaling results using coarser-scale remotely sensed products combined ability of measuring and mapping crown cover also holds great potential to use TLS data for calibrating and upscaling results using coarser-scale remotely sensed products.

The influence of voxel size and artifact reduction on the detection of vertical root fracture in endodontically treated teeth

Objective The aim of this study was to evaluate the effect of voxel size and artefact reduction (AR) on the identification of vertical root fractures (VRFs) in endodontically treated teeth. Methods A total of a hundred sound, extracted human mandibular single-rooted premolars were decoronated, after which root canal preparation was performed, canals were filled with gutta percha by single cone technique. Randomly selected fifty specimens were fractured, repositioned and glued together. The teeth were examined with cone beam computed tomography (CBCT) in five different voxel sizes (0.125, 0.200, 0.250, 0.300, and 0.400 voxels). Two scans were performed for each tooth, one with AR and one without AR. Two radiologists evaluated the CBCT scans. Results All voxel dimensions were successful in detecting VRFs in CBCT scans. But as the voxel size increased, the percentage of detecting VRFs decreased. High accuracy, sensitivity, specificity and predictive values were found for VRF detection on CBCT scans. Accuracy and sensitivity values decreased (from 100 to 82) while voxel dimensions increased (from 0.125 to 0.400). High-resolution images (0.125, 0.200, and 0.250 voxels) caused an increase in sensitivity for detection of VRFs. AR did not affect the accuracy, sensitivity, specificity and predictive values for VRF detection on CBCT scans. Conclusions High-resolution CBCT images resulted in an increase in sensitivity and specificity for detection of VRFs compared with lower-resolution CBCT images. The use of AR did not further improve its diagnostic potential.

Influence of voxel size on forest canopy height estimates using full-waveform airborne LiDAR data

BackgroundForest canopy height is a key forest structure parameter. Precisely estimating forest canopy height is vital to improve forest management and ecological modelling. Compared with discrete-return LiDAR (Light Detection and Ranging), small-footprint full-waveform airborne LiDAR (FWL) techniques have the capability to acquire precise forest structural information. This research mainly focused on the influence of voxel size on forest canopy height estimates.MethodsA range of voxel sizes (from 10.0 m to 40.0 m interval of 2 m) were tested to obtain estimation accuracies of forest canopy height with different voxel sizes. In this study, all the waveforms within a voxel size were aggregated into a voxel-based LiDAR waveform, and a range of waveform metrics were calculated using the voxel-based LiDAR waveforms. Then, we established estimation model of forest canopy height using the voxel-based waveform metrics through Random Forest (RF) regression method.Results and conclusionsThe results showed the voxel-based method could reliably estimate forest canopy height using FWL data. In addition, the voxel sizes had an important influence on the estimation accuracies (R2 ranged from 0.625 to 0.832) of forest canopy height. However, the R2 values did not monotonically increase or decrease with the increase of voxel size in this study. The best estimation accuracy produced when the voxel size was 18 m (R2 = 0.832, RMSE = 2.57 m, RMSE% = 20.6%). Compared with the lowest estimation accuracy, the R2 value had a significant improvement (33.1%) when using the optimal voxel size. Finally, through the optimal voxel size, we produced the forest canopy height distribution map for this study area using RF regression model. Our findings demonstrate that the optimal voxel size need to be determined for improving estimation accuracy of forest parameter using small-footprint FWL data.

The effect of SSD, Field size, Energy and Detector type for Relative Output Factor measurement in small photon beams as compared with Monte Carlo simulation

Abstract Introduction: Small fields photon dosimetry is associated with many problems. Using the right detector for measurement plays a fundamental role. This study investigated the measurement of relative output for small photon fields with different detectors. It was investigated for three-photon beam energies at SSDs of 90, 95, 100 and 110 cm. As a benchmark, the Monte Carlo simulation was done to calculate the relative output of these small photon beams for the dose in water. Materials and Methods: 6, 10 and 15 MV beams were delivered from a Synergy LINAC equipped with an Agility 160 multileaf collimator (MLC). A CC01 ion chamber, EFD-3G diode, PTW60019 microdiamond, EBT2 radiochromic film, and EDR2 radiographic film were used to measure the relative output of the linac. Measurements were taken in water for the CC01 ion chamber, EFD-3G diode, and the PTW60019. Films were measured in water equivalent RW3 phantom slabs. Measurements were made for 1 × 1, 2 × 2, 3 × 3, 4 × 4, 5 × 5 and a reference field of 10 × 10 cm2. Field sizes were defined at 100cm SSD. Relative output factors were also compared with Monte Carlo (MC) simulation of the LINAC and a water phantom model. The influence of voxel size was also investigated for relative output measurement. Results and Discussion: The relative output factor (ROF) increased with energy for all fields large enough to have lateral electronic equilibrium (LEE). This relation broke down as the field sizes decreased due to the onset of lateral electronic disequilibrium (LED). The high-density detector, PTW60019 gave the highest ROF for the different energies, with the less dense CC01 giving the lowest ROFs. Conclusion: These are results compared to MC simulation, higher density detectors give higher ROF values. Relative to water, the ROF measured with the air-chamber remained virtually unchanged. The ROFs, as measured in this study showed little variation due to increased SSDs. The effect of voxel size for the Monte Carlo calculations in water does not lead to significant ROF variation over the small fields studied.

Size and shape matter: The impact of voxel geometry on the identification of small nuclei.

How, and to what extent do size and shape of a voxel measured with magnetic resonance imaging (MRI) affect the ability to visualize small brain nuclei? Despite general consensus that voxel geometry affects volumetric properties of regions of interest, particularly those of small brain nuclei, no quantitative data on the influence of voxel size and shape on labeling accuracy is available. Using simulations, we investigated the selective influence of voxel geometry by reconstructing simulated ellipsoid structures with voxels varying in shape and size. For each reconstructed ellipsoid, we calculated differences in volume and similarity between the labeled volume and the predefined dimensions of the ellipsoid. Probability functions were derived from one or two individual raters and a simulated ground truth for reference. As expected, larger voxels (i.e., coarser resolution) and increasing anisotropy results in increased deviations of both volume and shape measures, which is of particular relevance for small brain structures. Our findings clearly illustrate the anatomical inaccuracies introduced by the application of large and/or anisotropic voxels. To ensure deviations occur within the acceptable range (Dice coefficient scores; DCS > 0.75, corresponding to < 57% volume deviation), the volume of isotropic voxels should not exceed 5% of the total volume of the region of interest. When high accuracy is required (DCS > 0.90, corresponding to a < 19% volume deviation), the volumes of isotropic voxels should not exceed 0.08%, of the total volume. Finally, when large anisotropic factors (>3) are used, and the ellipsoid is orthogonal to the slice axes, having its long axis in the imaging plane, the voxel volume should not exceed 0.005% of the total volume. This allows sufficient compensation of anisotropy effects, in order to reach accuracy in the acceptable range (DCS > 0.75, corresponding to >57% volume deviation).

Important queries for the airway analysis in cone-beam computed tomography scans: Threshold tool and voxel size protocol

Context: There is an expansion of the use of cone-beam computed tomography (CBCT) for maxillofacial diagnosis. However, some researchers have demonstrated inconsistencies between the results of airway analysis tools. Aim: This study aims to analyze the threshold tool presented in postprocessing software for airway volume estimation and the influence of voxel size in these measurements. Methods: Three hundred and sixteen-selected CBCT scans (0.2, 0.25, and 0.4 voxel sizes) were retrospectively analyzed. A trained and calibrated examiner performed the volume measurements in specific sites in upper airway at 25 and chosen threshold tool using the Dolphin Software. Statistical Analysis Used: Analysis of variance (ANOVA) was used to compare the thresholds for each voxel and the differences between the preset and the chosen thresholds, while paired t-test to compare differences between the chosen thresholds for voxel size groups. Results: The threshold values range from 26 to 43. The mean of the threshold selected for voxel 0.4 was significantly lower than the mean thresholds of 0.2 mm to 0.25 mm voxel. Small volumes were obtained with the preset threshold tool for all voxel sizes when compared with the chosen threshold. The mean of differences in volumes between preset and chosen threshold decreased with the increase of voxel size. Conclusion: The voxel size protocol influenced the threshold value choice for volume measurements in upper airway analysis. The thresholds near to 30 seem better filling the airway space.

Estimating Leaf Area Density of Individual Trees Using the Point Cloud Segmentation of Terrestrial LiDAR Data and a Voxel-Based Model

The leaf area density (LAD) within a tree canopy is very important for the understanding and modeling of photosynthetic studies of the tree. Terrestrial light detection and ranging (LiDAR) has been applied to obtain the three-dimensional structural properties of vegetation and estimate the LAD. However, there is concern about the efficiency of available approaches. Thus, the objective of this study was to develop an effective means for the LAD estimation of the canopy of individual magnolia trees using high-resolution terrestrial LiDAR data. The normal difference method based on the differences in the structures of the leaf and non-leaf components of trees was proposed and used to segment leaf point clouds. The vertical LAD profiles were estimated using the voxel-based canopy profiling (VCP) model. The influence of voxel size on the LAD estimation was analyzed. The leaf point cloud’s extraction accuracy for two magnolia trees was 86.53% and 84.63%, respectively. Compared with the ground measured leaf area index (LAI), the retrieved accuracy was 99.9% and 90.7%, respectively. The LAD (as well as LAI) was highly sensitive to the voxel size. The spatial resolution of point clouds should be the appropriate estimator for the voxel size in the VCP model.

A Monte Carlo study of the effect of an ultrasound transducer on surface dose during intrafraction motion imaging for external beam radiation therapy

The aim of this study was to estimate changes in surface dose due to the presence of the Clarity Autoscan™ ultrasound (US) probe during prostate radiotherapy using Monte Carlo (MC) methods. MC models of the Autoscan US probe were developed using the BEAMnrc/DOSXYZnrc code based on kV and MV CT images. CT datasets were converted to voxelized mass density phantoms using a CT number-to-mass density calibration. The dosimetric effect of the probe, in the contact region (an 8 mm × 12 mm single layer of voxels), was investigated using a phantom set-up mimicking two scenarios (a) a transperineal imaging configuration (radiation beam perpendicular to the central US axial direction), and (b) a transabdominal imaging configuration (radiation beam parallel to the central US axial direction). For scenario (a), the dosimetric effect was evaluated as a function of the probe to inferior radiation field edge distance. Clinically applicable distances from 5 mm separation to 2 mm overlap were determined from the radiotherapy plans of 27 patients receiving Clarity imaging. Overlaps of 3 to 14 (1 to 3 SD) mm were also considered to include the effect of interfraction motion correction. The influence of voxel size on surface dose estimation was investigated. Approved clinical plans from two prostate patients were used to simulate worst-case dosimetric impact of the probe when large couch translations were applied to correct for interfraction prostate motion. The dosimetric impact of both the MV and kV probe models agreed within ±2% for both beam configurations. For scenario (a) and 1 mm voxel model, the probe gave mean dose increases of 1.2% to 4.6% (of the dose at isocenter) for 5 mm separation to 0 mm overlap in the probe-phantom contact region, respectively. This increased to 27.5% for the largest interfraction motion correction considered (14 mm overlap). For separations of ≥ 2 mm dose differences were < 2%. Simulated dose perturbations were found to be superficial; for the 14 mm overlap the dose increase reduced to < 3% at 5.0 mm within the phantom. For scenario (b), dose increases due to the probe were < 5% in all cases. The dose increase was underestimated by up to ~13% when the voxel size was increased from 1 mm to 3 mm. MC simulated dose to the PTV and OARs for the two clinical plans considered showed good agreement with commercial treatment planning system results (within 2%). Mean dose increases due to the presence of the probe, after the maximum interfraction motion correction, were ~16.3% and ~8.0%, in the contact region, for plan 1 and plan 2, respectively. The presence of the probe results in superficial dose perturbations for patients with an overlap between the probe and the radiation field present in either the original treatment plan or due to translation of the radiation field to simulate correction of interfraction internal prostate motion.

Influence of voxel size and scan field of view on fracture-like artifacts from gutta-percha obturated endodontically treated teeth on cone-beam computed tomography images

To determine the optimal scan settings (scan mode and position of field of view [FOV]) for cone beam computed tomography to reduce root fracture-like artifacts that are often observed in teeth filled with gutta-percha cones (GPCs). Fracture-like artifacts that appeared on cone beam computed tomography images of 9 extracted human mandibular premolars filled with GPCs were analyzed using I-mode (FOV, 102mm; voxel size, 0.2mm) and D-mode (FOV, 51mm; voxel size, 0.1mm) settings. The artificial lines were more obvious in I-mode than in D-mode. Increased distance between the center of the FOV and the GPCs produced stronger artificial lines in both I-mode and D-mode. To reduce fracture-like artifacts, it is critical to use a mode with small voxel size and to place the target tooth in the center of the FOV.

Influence of voxel size on the diagnostic ability of cone-beam computed tomography to evaluate simulated root perforations

Influence of voxel size on the diagnostic ability of cone-beam computed tomography to evaluate simulated root perforations

Influence of voxel size on the diagnostic ability of cone-beam computed tomography to evaluate simulated root perforations

Objectives This study aimed to assess the use of different voxel sizes of a cone-beam computed tomography (CBCT) unit for detecting root perforations of different sizes and locations ex vivo and to compare the diagnostic possibilities of CBCT with those of periapical radiography (PR).

Influence of voxel size on specific absorbed fractions and S-values in a mouse voxel phantom

Photon and electron specific absorbed fractions (SAFs) and S-values have been evaluated using mouse voxel phantoms. In voxel phantoms, it is important to choose the voxel size carefully since it affects the accuracy of results. In this study, two mouse voxel phantoms were constructed, with cubic voxels, one with 0.1-mm sides and the other with 0.4-mm sides. The sources were considered to be distributed uniformly in the main organs and the radiation transport was simulated using the Monte Carlo code EGS4. It was found that the effect of voxel size on SAFs for self-irradiation was not high (<10 %) for electrons and photons. However, it was appreciable for cross-irradiation especially for electrons. The effect of voxel size was investigated on S-values for some beta emitters such as (131)I, (153)Sm, (188)Re and (90)Y.

Influence of Voxel Size in the Diagnostic Ability of Cone Beam Tomography to Evaluate Simulated External Root Resorption

This study assessed in vitro the diagnostic ability of cone beam computed tomography (CBCT) scans with different voxel resolutions in the detection of simulated external root resorption (ERR). For that purpose, 59 teeth were viewed through iCAT tomography (Imaging Sciences International, Inc, Hatfield, PA) following three protocols in which the variation was the voxel resolution (0.4, 0.3, and 0.2mm). A calibrated examiner blinded to the protocol assessed the images through the i-CAT View software (Imaging Sciences International, Inc). The chi-square statistical analysis did not show associations between voxel resolution, section plane, size of cavity, and radicular third. Sensitivity and specificity values were similar. However, likelihood ratio values of 6.4 for a 0.4-mm voxel, 16 for a 0.3-mm voxel, and 12 for a 0.2-mm voxel were found. It was concluded that CBCT is a reliable method for the investigation of simulated ERR, and a 0.3-mm voxel appeared to be the best protocol, associating good diagnostic performance with lower X-ray exposure.