Noise Power Spectrum Research Articles

Synthetization of high-dose images using low-dose CT scans.

Radiation dose reduction has been the focus of many research activities in x-ray CT. Various approaches were taken to minimize the dose to patients, ranging from the optimization of clinical protocols, refinement of the scanner hardware design, and development of advanced reconstruction algorithms. Although significant progress has been made, more advancements in this area are needed to minimize the radiation risks to patients. Reconstruction algorithm-based dose reduction approaches focus mainly on the suppression of noise in the reconstructed images while preserving detailed anatomical structures. Such an approach effectively produces synthesized high-dose images (SHD) from the data acquired with low-dose scans. A representative example is the model-based iterative reconstruction (MBIR). Despite its widespread deployment, its full adoption in a clinical environment is often limited by an undesirable image texture. Recent studies have shown that deep learning image reconstruction (DLIR) can overcome this shortcoming. However, the limited availability of high-quality clinical images for training and validation is often the bottleneck for its development. In this paper, we propose a novel approach to generate SHD with existing low-dose clinical datasets that overcomes both the noise texture issue and the data availability issue. Our approach is based on the observation that noise in the image can be effectively reduced by performing image processing orthogonal to the imaging plane. This process essentially creates an equivalent thick-slice image (TSI), and the characteristics of TSI depend on the nature of the image processing. An advantage of this approach is its potential to reduce impact on the noise texture. The resulting image, however, is likely corrupted by the anatomical structural degradation due to partial volume effects. Careful examination has shown that the differential signal between the original and the processed image contains sufficient information to identify regions where anatomical structures are modified. The differential signal, unfortunately, contains significant noise and has to be removed. The noise removal can be accomplished by performing iterative noise reduction to preserve structural information. The processed differential signal is subsequently subtracted from TSI to arrive at SHD. The algorithm was evaluated extensively with phantom and clinical datasets. For better visual inspection, difference images between the original and SHD were generated and carefully examined. Negligible residual structure could be observed. In addition to the qualitative inspection, quantitative analyses were performed on clinical images in terms of the CT number consistency and the noise reduction characteristics. Results indicate that no CT number bias is introduced by the proposed algorithm. In addition, noise reduction capability is consistent across different patient anatomical regions. Further, simulated water phantom scans were utilized in the generation of the noise power spectrum (NPS) to demonstrate the preservation of the noise-texture. We present a method to generate SHD datasets from regularly acquired low-dose CT scans. Images produced with the proposed approach exhibit excellent noise-reduction with the desired noise-texture. Extensive clinical and phantom studies have demonstrated the efficacy and robustness of our approach. Potential limitations of the current implementation are discussed and further research topics are outlined.

Quality improvement of images with metal artifact reduction using a noise recovery technique in computed tomography.

In metal artifact reduction (MAR) in computed tomography (CT) based on projection data inpainting, X-ray photon noise has not been considered in the inpainting process. This study aims to assess the effectiveness of a MAR technique incorporating noise recovery in such projection data regions, compared with existing MAR techniques based on projection data normalization (NMAR), including one with frequency splitting (FSNMAR). Phantoms simulating hip prostheses and dental fillings were scanned using a 64-row multi slice CT scanner. The projection data was processed by NMAR and NMAR with noise recovery (NRNMAR); the processed data was sent back to the CT system for reconstruction. For the phantoms and clinical cases with hip prostheses and dental fillings, images were reconstructed without MAR, and with NMAR, NRNMAR, and FSNMAR (incorporated in the CT system). To validate the efficacy of noise recovery, noise power spectra (NPSs) were measured from the images of the hip prosthesis phantom with and without metals. The artifact index (AI) was compared between NRNMAR and FSNMAR. The resultant NPSs of NRNMAR were very similar to those of phantom images with no metals, endorsing the efficacy of noise recovery. The NMAR images had unnatural noise textures and FSNMAR caused additional streaks. NRNMAR exhibited some significant improvements in these respects: It reduced the AI by as much as 66.2-88.6% compared to FSNMAR, except for the case of a unilateral prosthesis. In conclusion, NRNMAR, which simply adds white noise to the projection data, would be effective in improving the quality of CT images with metal artifacts reduction.

Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study

PurposeThe purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol. Materials and methodsAcquisitions were performed using the CT ACR 464 phantom at three dose levels (volume CT dose indexes: 7.1/5.2/3.1 mGy) using a prospective cardiac CT protocol. Raw data were reconstructed using the three levels of AiCE and PIQE (Mild, Standard and Strong). The noise power spectrum (NPS) and task-based transfer function (TTF) for bone and acrylic inserts were computed. The detectability index (d’) was computed to model the detectability of the coronary lumen (350 Hounsfield units and 4-mm diameter) and non-calcified plaque (40 Hounsfield units and 2-mm diameter). ResultsNoise magnitude values were lower with PIQE than with AiCE (−13.4 ± 6.0 [standard deviation (SD)] % for Mild, -20.4 ± 4.0 [SD] % for Standard and -32.6 ± 2.6 [SD] % for Strong levels). The average NPS spatial frequencies shifted towards higher frequencies with PIQE than with AiCE (21.9 ± 3.5 [SD] % for Mild, 20.1 ± 3.0 [SD] % for Standard and 12.5 ± 3.5 [SD] % for Strong levels). The TTF values at fifty percent (f50) values shifted towards higher frequencies with PIQE than with AiCE for acrylic inserts but, for bone inserts, f50 values were found to be close. Whatever the dose and DLR level, d’ values of both simulated cardiac lesions were higher with PIQE than with AiCE. For the simulated coronary lumen, d’ values were better by 35.1 ± 9.3 (SD) % on average for all dose levels for Mild, 43.2 ± 5.0 (SD) % for Standard, and 62.6 ± 1.2 (SD) % for Strong levels. ConclusionCompared to AiCE, PIQE reduced noise, improved spatial resolution, noise texture and detectability of simulated cardiac lesions. PIQE seems to have a greater potential for dose reduction in cardiac CT acquisition.

Detective quantum efficiency of a double-layered detector for dual-energy x-ray imaging

A sandwich-like double-layered detector can perform dual-energy imaging (DEI) using a single x-ray exposure without object motion artifacts. The energy separation between measurements obtained from the front and rear-detector layers can be tuned by introducing an x-ray beam-attenuating material between them. However, the design of the interdetector filter significantly influences dose efficiency by altering the number of x-ray photons reaching the rear-detector layer within the sandwich detector. Since the sandwich detector typically incorporates phosphors of differing thicknesses for its two detector layers, it exhibits a unique spatial resolution characteristic in the reconstructed dual-energy (DE) images. To comprehensively assess detector performance in terms of design (filter) and operation (reconstruction), we established a framework that describes the dual-energy detective quantum efficiency (DE-DQE) using linear-systems theory. The developed DE-DQE model was validated through comparison with measurements. The agreement between the modulation-transfer functions was reasonable, and the correspondence between noise-power spectra was excellent. This proposed DE-DQE concept is universally applicable to any linearly operating DE system and holds a significant value in enhancing the performance of sandwich detectors or ensuring their optimal operation.

Effects of Anti-Scatter Grid on Noise Power Spectrum at Different Dose Levels in Digital Mammography

Amaç: Gürültü güç spektrumu (NPS), dijital bir görüntüdeki gürültüyü frekans uzayında karakterize etmek için kullanılan önemli bir kalite kontrol parametresidir. NPS'nin ilgi alanı içerisindeki (ROI) ortalama piksel değerlerinin karesine bölünmesiyle normalize NPS (NNPS) hesaplanır ve NNPS medikal bir görüntüdeki gürültü analizi için kullanılmaktadır. Bu çalışmanın amacı, NNPS analizinde saçılma önleyici grid kullanımının NNPS’e etkisini belirlemektir. Yöntemler: NNPS ölçümleri, 8 µGy ile 400 µGy arasında değişen farklı doz seviyeleri için beş Fujifilm Amulet Innovality tüm-alan dijital mamografi (FFDM) sisteminde gridli ve gridsiz olarak gerçekleştirildi. Belirlenen her bir doz seviyesi için üç farklı homojen dedektör görüntüsü alındı. Elde edilen tüm ham dedektör görüntüleri ImageJ yazılımı COQ eklentisi kullanılarak değerlendirilmiştir. NNPS'deki değişimleri belirlemek için bağıl fark tercih edilmiştir. Sonuçlar: Gridli ve gridsiz elde edilen görüntüler arasındaki maksimum bağıl fark 20.31 µGy doz seviyesi için 0.5 mm-1 uzaysal frekansta 2.63 olarak bulunmuştur. Tartışma: Sonuçlar, artan doz seviyesi ile NNPS’nin azaldığını, grid kullanıldığında ise dedektöre ulaşan ortalama x-ışını foton sayısındaki azalma nedeniyle NNPS'nin arttığını göstermiştir

PENGARUH PARAMETER CT UNTUK OPTIMISASI DOSIS RADIASI DAN KUALITAS CITRA CT SCAN PADA PEMERIKSAAN KEPALA DAN ABDOMEN DI RS SENTRA MEDIKA CIBINONG

Radiation dose optimization in head and abdomen examinations is an effort to ensure safety and minimize the risks of exposure to CT Scan radiation. Therefore, various efforts are necessary to reduce radiation doses. This study aims to obtain an optimal radiation dose while maintaining image quality. The optimization efforts were carried out by the radiology team at RS Sentra Medika Cibinong using the CT Scan GE OPTIMA 660. The method involved scanning head and abdomen phantoms using optimization factors (Noise Index, Slice Thickness, Pitch, and Rotation Time) and then analyzing the images for noise uniformity, MTF (Modulation Transfer Function), and NPS (Noise Power Spectrum) while recording radiation dose in terms of CTDIvol and DLP. Based on the research data using GE standard Head protocol and respective optimizations, the radiation dose values obtained were CTDIVol = 68 mGy; DLP = 2042 mGy.cm and CTDIVol = 48 mGy; DLP = 1662 mGy.cm. Furthermore, the image quality produced by the GE standard Head protocol and respective optimizations resulted in MTF values of 0.55 (1/mm) and 0.91 (1/mm), noise uniformity of 0.6 HU and 1.6 HU, and NPS deviation of 8.7%. Regarding the Abdomen protocol, using GE standard and respective optimizations, the radiation dose values obtained were CTDIVol = 32 mGy; DLP = 1025 mGy.cm and CTDIVol = 22 mGy; DLP = 955 mGy.cm. Additionally, the image quality produced by the GE standard Abdomen protocol and respective optimizations resulted in MTF values of 0.58 (1/mm) and 0.6 (1/mm), noise uniformity of 0.6 HU and 1.6 HU, and NPS deviation of 7.6%. Thus, the protocols using optimization factors were proven to reduce radiation dose by approximately 41.6-45.4% while maintaining image quality compared to the GE standard protocol, which focuses more on improving image quality rather than optimizing the radiation dose received by patients. Keywords: CT Scan, Optimization Factors, Image Quality, CTDIvol, DLP.

Whitening method for passive water pipeline assessment using ambient noise

Previous studies have verified the feasibility of using ambient noise in water pipeline networks as natural signals to assess pipeline condition passively. This passive technology uses correlation peaks of the ambient noise as characteristics to identify pipe faults and deterioration, and it requires the noise power spectrum density (PSD) to be adequately whitened. However, conventional noise whitening methods cannot provide sufficient whitening for the ambient noise in water pipelines due to the significant noise PSD variations that are unevenly distributed across the wide relative bandwidth of the noise signals. This paper proposes a tailored whitening process for water pipeline ambient noise by applying logarithmic transforms on both the magnitude and frequency axes to compresses the large dynamic range of the PSD magnitude and bandwidth. Numerical simulations and field experiment results have verified that the proposed method can effectively whiten the noise signals in water pipelines, and accurately restore the amplitude of correlation peaks to be consistent with the theoretical derivation using white noise assumptions. The theoretical derivation also reveals the relation between the amplitudes of correlation peaks and the noise spatial distribution, fault distance and its reflection/transmission coefficients. The feasibility of estimating the reflection coefficient of pipe faults from the correlation results with appropriately whitened noise is also investigated in this paper.

Ensuring fair assessment of solid-state nanopore sensors with reporting baseline current

In developing solid-state nanopore sensors for single molecule detection, comprehensive evaluation of the nanopore quality is important. Existing studies typically rely on comparing the noise root mean square or power spectrum density values. Nanopores exhibiting lower noise values are generally considered superior. This evaluation is valid when the single molecule signal remains consistent. However, the signal can vary, as it is strongly related to the solid-state nanopore size, which is hard to control during fabrication consistently. This work emphasized the need to report the baseline current for evaluating solid-state nanopore sensors. The baseline current offers insight into several experimental conditions, particularly the nanopore size. Our experiments show that a nanopore sensor with more noise is not necessarily worse when considering the signal-to-noise ratio (SNR), particularly when the pore size is smaller. Our findings suggest that relying only on noise comparisons can lead to inaccurate evaluations of solid-state nanopore sensors, considering the inherent variability in fabrication and testing setups among labs and measurements. We propose that future studies should include reporting baseline current and sensing conditions. Additionally, using SNR as a primary evaluation tool for nanopore sensors could provide a more comprehensive understanding of their performance.

A phantom based evaluation of the clinical imaging performance of electronic portal imaging devices

PurposeIn this study an evaluation of the imaging performance of an electronic portal imaging device (EPID) is presented. The evaluation performed employing the QC-3V image quality phantom. MethodsAn EPID system of a 6 MV LINAC, was used to obtain images of a QC-3V EPID phantom. The X-ray source to phantom distance was 100 cm and the field size was 15x15 cm2. The irradiation conditions comprised Dose Rates (DR) of 200, 400 and 600 for a 2 MU–100 MU range. The Contrast Transfer Function (CTF), the Noise Power Spectrum (NPS), the Normalized Noise Power Spectrum (NNPS) and the Contrast-to-Noise Ratio (CNR) were studied. In addition, an alternative factor showing a frequency related output signal-to-noise ratio (SNR), the Signal-to-Noise-Frequency Response (SNFR), has been introduced. SNFR is a comprehensive quality index, easily determined in clinical environment. ResultsThe CTF curves were found comparable to each other. The lowest values were measured at 2 MU and 200 MU/min. Concerning the NPS and NNPS graphs it was found that the values decrease up to approximately 0.3 lp/mm and demonstrate a white noise shape afterwards. SNFR values were found reducing with spatial frequency. Highest CNR were found between the region 7 and 11 of the phantom. ConclusionsThe influence of MU and DR on EPID performance were investigated. Image quality was assessed using the QC-3V phantom. The presented results can lead to image quality amelioration and act supportively to current image quality control routine protocols.

Signal and noise analysis of a metal oxide transistor-based flat-panel detector

Recently, metal-oxide thin-film transistor (TFT)-based flat-panelx-ray detectors have attracted attention owing to their fast readouttimes and low noise characteristics. We empirically analyzed the signaland noise characteristics of an indium gallium zinc oxide (IGZO) TFT-baseddetector in comparison with those of a conventional hydrogenated amorphoussilicon (a-Si:H) TFT-based detector. We compared the large-areasignal transfer functions of the detectors as a function of air kermaat their entrance surfaces. Signal and noise performances were evaluatedby measuring the modulation-transfer function, noise-power spectrum,and detective quantum efficiency (DQE). The low-dose imaging capabilityof the detectors was assessed by investigating the large-area or zero-frequencyDQE as a function of air kerma. Herein, we evaluated the value ofthe IGZO detector in terms of dose efficiency in comparison to theconventional a-Si:H detector.

Investigating sound absorption in rail tunnels using wave decomposition

Acoustic noise in trains is a more prevalent problem in tunnels as compared to open track scenarios. This is mainly due to less acoustic radiation relative to increasing contributions of reflections and reverberation. Sound absorbing panels on a tunnel wall and in the track four-foot perform better above 1 kHz with absorption coefficients larger than 0.8. To investigate sound absorption below 1 kHz, we employ wave decomposition into incidence, reflection and absorption components for a section of a given underground tunnel design. A Finite Element (FE) 2D model of a carriage and tunnel is developed, representing a tangent portion of a rail track and including the noise power spectra from the rail-wheel interactions for three different roughness scenarios. The FE model, compared to a Ray Tracing one, provides precisely imposed boundary conditions and the pressure field of the entire tunnel interior. Our results can identify the performance of current panels, absorbing significantly less noise power in the lower frequency range, especially within the 0.3–0.5 kHz interval. The insights from wave decomposition analysis can lead to solutions to increase absorption by changing the reflection pattern below 1 kHz band, improving the passenger comfort during a longer train ride.

Impact of Phantom Size on Low-Energy Virtual Monoenergetic Images of Three Dual-Energy CT Platforms.

The purpose of this study was to compare the quality of low-energy virtual monoenergetic images (VMIs) obtained with three Dual-Energy CT (DECT) platforms according to the phantom diameter. Three sections of the Mercury Phantom 4.0 were scanned on two generations of split-filter CTs (SFCT-1st and SFCT-2nd) and on one Dual-source CT (DSCT). The noise power spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were assessed on VMIs from 40 to 70 keV. The highest noise magnitude values were found with SFCT-1st and noise magnitude was higher with DSCT than with SFCT-2nd for 26 cm (10.2% ± 1.3%) and 31 cm (7.0% ± 2.5%), and the opposite for 36 cm (-4.2% ± 2.5%). The highest average NPS spatial frequencies and TTF values at 50% (f50) values were found with DSCT. For all energy levels, the f50 values were higher with SFCT-2nd than SFCT-1st for 26 cm (3.2% ± 0.4%) and the opposite for 31 cm (-6.9% ± 0.5%) and 36 cm (-5.6% ± 0.7%). The lowest d' values were found with SFCT-1st. For all energy levels, the d' values were lower with DSCT than with SFCT-2nd for 26 cm (-6.2% ± 0.7%), similar for 31 cm (-0.3% ± 1.9%) and higher for 36 cm (5.4% ± 2.7%). In conclusion, compared to SFCT-1st, SFCT-2nd exhibited a lower noise magnitude and higher detectability values. Compared with DSCT, SFCT-2nd had a lower noise magnitude and higher detectability for the 26 cm, but the opposite was true for the 36 cm.

Physical characteristics of deep learning-based image processing software in computed tomography: a phantom study.

This study aimed to assess the image characteristics of deep-learning-based image processing software (DLIP; FCT PixelShine, FUJIFILM, Tokyo, Japan) and compare it with filtered back projection (FBP), model-based iterative reconstruction (MBIR), and deep-learning-based reconstruction (DLR). This phantom study assessed the object-specific spatial resolution (task-based transfer function [TTF]), noise characteristics (noise power spectrum [NPS]), and low-contrast detectability (low-contrast object-specific contrast-to-noise ratio [CNRLO]) at three different output doses (standard: 10mGy; low: 3.9mGy; ultralow: 2.0mGy). The processing strength of DLIPFBP with A1, A4, and A9 was compared with those of FBP, MBIR, and DLR. The standard dose with high-contrast TTFs of DLIPFBP exceeded that of FBP. Low-contrast TTFs were comparable to or lower than that of FBP. The NPS peak frequency (fP) of DLIPFBP shifts to low spatial frequencies of up to 8.6% at ultralow doses compared to the standard FBP dose. MBIR shifted the most fP compared to FBP-a marked shift of up to 49%. DLIPFBP showed a CNRLO equal to or greater than that of DLR in standard or low doses. In contrast, the CNRLO of the DLIPFBP was equal to or lower than that of the DLR in ultralow doses. DLIPFBP reduced image noise while maintaining a resolution similar to commercially available MBIR and DLR. The slight spatial frequency shift of fP in DLIPFBP contributed to the noise texture degradation suppression. The NPS suppression in the low spatial frequency range effectively improved the low-contrast detectability.

A comparative analysis of head computed tomography scans protocols and thyroid dosimetry

Computed Tomography (CT) is currently one of the most widely used imaging modalities for disease identification, benefiting numerous patients with its advanced technology. However, there is a concern regarding its inappropriate use, which can lead to higher radiation doses in patients and consequently increase the potential risks of developing stochastic effects. Therefore, it is crucial to explore methodologies for optimizing patient doses, particularly in organs with higher radiosensitivity. Within this context, the aim of the proposed study is to compare absorbed dose and noise among different head CT scans using a polymethylmethacrylate (PMMA) phantom, proposing a better relationship between image quality and dose reduction for protocol and thyroid in head CT scans. The tests were conducted using head acquisition protocols on two CT scanners: a GE LightSpeed VCT with 64 channels and a Toshiba CT with 4 channels. The PMMA head-neck phantom consisted of two cylinders, one with a diameter of 16 cm and another with a diameter of 11 cm was used in this work. Radiochromic films and an ionization chamber were also utilized. The study evaluated discrepancies in CT scans, including Noise Power Spectrum (NPS), dose profiles, and punctual doses in thyroid. Protocols P1A and P2B had the lowest and highest CTDIvol values, respectively. Radiochromic films facilitated precise dose analysis, identifying position 12 with the highest dose. NPS analysis revealed variations in noise distribution between the protocols.

Spectral performance of two split-filter dual-energy CT systems: A phantom study.

Recently, a second generation of split filter dual-energy CT (SFCT) platform has been developed. The thicknesses of the gold and tin filters used to obtain both low- and high-energy spectra have been changed. These differences in filter thickness may affect the spectral separation between the two spectra and thus the quality of spectral images. To compare the spectral performance of two Split-Filter Dual-Energy CT systems (SFCT-1st and SFCT-2nd ) on virtual monoenergetic images (VMIs) and iodine map. A Multi-Energy CT phantom was scanned on two SFCT with a tube voltage of 120 kVp for both systems (SFCT-1st -120 and SFCT-2nd -120) and 140 kVp only for the second generation (SFCT-2nd -140). Acquisitions were performed on the phantom with a CTDIvol close to 11 mGy. Noise power spectrum (NPS) and task-based transfer function (TTF) were evaluated on VMIs from 40 to 70keV. A detectability index (d') was computed to assess the detection of two contrast-enhanced lesions on VMIs. Hounsfield Unit (HU) accuracy was assessed on VMIs and the accuracy of iodine concentration was assessed on iodine maps. For all keV, noise magnitude values were lower with the SFCT-2nd -120 than with the SFCT-1st -120 (on average: -22.5±2.9%) and higher with the SFCT-2nd -140 than with the SFCT-2nd -120 (on average: 25.0±6.2%). Average NPS spatial frequencies (fav ) were lower with the SFCT-1st -120 than with the SFCT-2nd -120 (-6.0±0.5%) and the SFCT-2nd -140 (-3.6±1.6%). Similar TTF50% values were found for both systems and both kVp for blood and iodine inserts at 2mg/mL (0.29±0.01mm-1 ) and at 4mg/mL (0.31±0.01mm-1 ). d' values peaked at 40keV for the SFCT-2nd and at 70keV for the SFCT-1st . Highest d' values were found for the SFCT-2nd -120 for both simulated lesions. Accuracy of HU values and iodine concentration was higher with the SFCT-2nd than with the SFCT 1st . Compared to the SFCT-1st , with similar spatial resolution and noise texture values, the SFCT-2nd -120 exhibited the lowest values for noise magnitude, the highest detectability index values, and more accurate HU values and iodine concentrations.

Development, validation, and simplification of a scanner-specific CT simulator.

Simulated computed tomography (CT) images allow for knowledge of the underlying ground truth and for easy variation of imaging conditions, making them ideal for testing and optimization of new applications or algorithms. However, simulating all processes that affect CT images can result in simulations that are demanding in terms of processing time and computer memory. Therefore, it is of interest to determine how much the simulation can be simplified while still achieving realistic results. To develop a scanner-specific CT simulation using physics-based simulations for the position-dependent effects and shift-invariant image corruption methods for the detector effects. And to investigate the impact on image realism of introducing simplifications in the simulation process that lead to faster and less memory-demanding simulations. To make the simulator realistic and scanner-specific, the spatial resolution and noise characteristics, and the exposure-to-detector output relationship of a clinical CT system were determined. The simulator includes a finite focal spot size, raytracing of the digital phantom, gantry rotation during projection acquisition, and finite detector element size. Previously published spectral models were used to model the spectrum for the given tube voltage. The integrated energy at each element of the detector was calculated using the Beer-Lambert law. The resulting angular projections were subsequently corrupted by the detector modulation transfer function (MTF), and by addition of noise according to the noise power spectrum (NPS) and signal mean-variance relationship, which were measured for different scanner settings. The simulated sinograms were reconstructed on the clinical CT system and compared to real CT images in terms of CT numbers, noise magnitude using the standard deviation, noise frequency content using the NPS, and spatial resolution using the MTF throughout the field of view (FOV). The CT numbers were validated using a multi-energy CT phantom, the noise magnitude and frequency were validated with a water phantom, and the spatial resolution was validated with a tungsten wire. These metrics were compared at multiple scanner settings, and locations in the FOV. Once validated, the simulation was simplified by reducing the level of subsampling of the focal spot area, rotation and of detector pixel size, and the changes in MTFs were analyzed. The average relative errors for spatial resolution within and across image slices, noise magnitude, and noise frequency content within and across slices were 3.4%, 3.3%, 4.9%, 3.9%, and 6.2%, respectively. The average absolute difference in CT numbers was 10.2HU and the maximum was 22.5HU. The simulation simplification showed that all subsampling can be avoided, except for angular, while the error in frequency at 10% MTF would be maximum 16.3%. The simulation of a scanner-specific CT allows for the generation of realistic CT images by combining physics-based simulations for the position-dependent effects and image-corruption methods for the shift-invariant ones. Together with the available ground truth of the digital phantom, it results in a useful tool to perform quantitative analysis of reconstruction or post-processing algorithms. Some simulation simplifications allow for reduced time and computer power requirements with minimal loss of realism.

Image Quality and Radiation Dose of Conventional and Wide-Field High-Resolution Cone-Beam Computed Tomography for Cerebral Angiography: A Phantom Study.

There has been an increase in the use of interventional neuroradiology procedures because of their non-invasiveness compared to surgeries and the improved image quality of fluoroscopy, digital subtraction angiography, and rotational angiography. Although cone-beam computed tomography (CBCT) images are inferior to multi-detector CT images in terms of low-contrast detectability and lower radiation doses, CBCT scans are frequently performed because of their accessibility. This study aimed to evaluate the image quality and radiation dose of two different high-resolution CBCTs (HR CBCT): conventional (C-HR CBCT) and wide-field HR CBCT (W-HR CBCT). The modulation transfer function (MTF), noise power spectrum (NPS), and contrast-to-noise ratio (CNR) were used to evaluate the image quality. On comparing the MTF of C-HR CBCT with a 256 × 256 matrix and that of W-HR CBCT with a 384 × 384 matrix, the MTF of W-HR CBCT with the 384 × 384 matrix was larger. A comparison of the NPS and CNR of C-HR CBCT with a 256 × 256 matrix and W-HR CBCT with a 384 × 384 matrix showed that both values were comparable. The reference air kerma values were equal for C-HR CBCT and W-HR CBCT; however, the value of the kerma area product was 1.44 times higher for W-HR CBCT compared to C-HR CBCT. The W-HR CBCT allowed for improved spatial resolution while maintaining the image noise and low-contrast detectability by changing the number of image matrices from 256 × 256 to 384 × 384. Our study revealed the image characteristics and radiation dose of W-HR CBCT. Given its advantages of low-contrast detectability and wide-area imaging with high spatial resolution, W-HR CBCT may be useful in interventional neuroradiology for acute ischemic stroke.

Evaluation of radiation dose and image quality for dental cone-beam computed tomography in pediatric patients

Children are sensitive to radiation; therefore, it is necessary to reduce radiation dose as much as possible in pediatric patients. In addition, it is crucial to investigate the optimal imaging conditions as they considerably affect the radiation dose. In this study, we investigated the effect of different imaging conditions on image quality and optimized the imaging conditions for dental cone-beam computed tomography (CBCT) examinations to diagnose ectopic eruptions and impacted teeth in children. To achieve our aims, we evaluated radiation doses and subjective and objective image quality. The CBCT scans were performed using 3D Accuitomo F17. All combinations of a tube voltage (90 kV), tube currents (1, 2, 3 mA), fields of view (FOVs) (4 × 4, 6 × 6 cm), and rotation angles (360°, 180°) were used. Dose-area product values were measured. SedentexCT IQ cylindrical phantom was used to physically evaluate the image quality. We used the modulation transfer function as an index of resolution, the noise power spectrum as an index of noise characteristics, and the system performance function as an overall evaluation index of the image. Five dentists visually evaluated the images from the head-neck phantom. The results showed that the image quality tended to worsen, and scores for visual evaluation decreased as tube currents, FOVs and rotation angles decreased. In particular, image noise negatively affected the delineation of the periodontal ligament space. The optimal imaging conditions were 90 kV, 2 mA, 4 × 4 cm FOV and 180° rotation. These results suggest that CBCT radiation doses can be significantly reduced by optimizing the imaging conditions.

Comparing eDQE and eNEQ metrics – is there an alternative approach to assessing image quality in digital mammography?

Abstract Introduction: Early detection of breast cancer requires high-quality mammographic images that have been made possible by the introduction of new technologies, such as full-field digital mammography (FFDM). In this new study, we perform extended measurements to calculate effective detective quantum efficiency (eDQE) and introduce effective noise equivalent quanta (eNEQ). Our aim was to show how these two metrics relate to the image quality of two digital mammography systems. Material and methods: Measurements were performed for a Siemens Mammomat Inspiration and a GE Senographe Pristina system. Each was equipped with an automatic exposure control (AEC) for use in a clinical setting. We used a polymethyl methacrylate (PMMA) phantom at thicknesses of 20, 30, 40 and 70 mm to cover the range of scatter conditions expected in mammography, with and without an anti-scatter grid. The Siemens system had an a-Se detector, and the GE system had an indirect-conversion detector. Measurements of Kerma were performed with Piranha Black 657 meter (RTI Electronics AB). The majority of our calculations were automated, using a modified version of our software. Results: For the two mammographic systems evaluated, we characterized physical quality parameters, such as effective modulation transfer function (eMTF), effective normalized noise power spectrum (eNNPS), eDQE and eNEQ for a wide range of exposures, phantom thicknesses, with and without an anti-scatter grid. Results are presented as a function of spatial frequency. A contrast-detail analysis was performed with a CDMAM 3.4 phantom with dedicated software (CDMAM analysis 1.5.5, NCCPM) and a set of different PMMA phantoms. Conclusions: We successfully demonstrated that the eNEQ metric can be used as a new option to evaluate image quality for images taken with and without a grid and with phantoms of different thicknesses for the Siemens and GE systems. These results were consistent with the results obtained from CDMAM.

Usefulness of Ag Additional Filter on Image Quality and Radiation Dose for Low-Dose Chest Computed Tomography.

This study aimed to evaluate the effect of a silver (Ag) additional filter on dose characteristics and image quality in low-dose chest computed tomography (CT). A dose evaluation phantom, physical evaluation phantom, and chest phantom were scanned with and without an Ag additional filter. The doses were adjusted so that the displayed the volume CT dose indexes (CTDI vol ) were from 0.3 to 1.6 mGy. For dose characteristics, the spectrum of photon energies and the measured CTDI vol were calculated for each scanning condition. For task-based image quality analysis, task transfer function, noise power spectrum, and system performance were evaluated. Streak artifacts, image noise, and contrast-to-noise ratio were quantified using a chest phantom. With the Ag additional filter, mean energy was 22% higher and the CTDI vol was approximately 30% lower than those without the Ag additional filter. The task transfer function and noise power spectrum with the Ag additional filter were lower than those without the Ag additional filter. The system performance with the Ag additional filter was similar to that without the Ag additional filter. The Ag additional filter reduced streak artifact near the lung apex and image noise in the lung fields. The contrast-to-noise ratio was slightly higher with the Ag additional filter than that without the Ag additional filter. The output dose and spatial resolution with the Ag additional filter were lower than those without the Ag additional filter. However, this filter helped reduce the radiation dose, image noise, and streak artifacts, particularly when scanning at ultralow doses.