Normalized Noise Power Spectrum Research Articles

Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging.

The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization. To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49kV with 1.5mm aluminum filter and at 65kV and 0.257mm copper filter. A 10mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5mm iodine disk detection task at 49, 55, 60, and 65kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4mm. At 49kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min=3.7%; max=8.5%). At 65kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min=11.4%; max=16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2=0.993) and 19.14µGy/mA (R2=0.996) at 49 and 65kV, respectively. For iodine detection, a 0.25mm-thick copper filter at 65kV was found optimal, outperforming the default technique by 90%. The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

Performance evaluation of six digital mammography systems

The strong advance in digital mammography as a tool for breast cancer screening requires that the new systems be characterized. Quality control protocols describe the methodology to evaluate systems performance. Detective quantum efficiency (DQE) is the most suitable parameter for describing the imaging performance of an X-ray imaging device. The objective of this study was to characterize in terms of DQE six digital mammography systems, at different detector air kerma (DAK) levels for a variety of beam qualities. A Carestream EHR-M3 CR detector, a small field digital mammography system Siemens Opdima, and full field digital mammography systems Planmed Clarity, GE Essential, GE Pristina and GE Crystal Nova were characterized using the European Guidelines protocol. Modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE were determined, for an extended detector air kerma range. Attenuated beam qualities (obtained by adding 2 mm Al to the corresponding beam qualities) used were 28 kV with anode/filter combination Mo/Mo for the EHR-M3, Opdima, Essential and Pristina systems; 28 kV W/Ag for the Clarity; 28 kV W/Rh for the Crystal Nova; 28 kV Mo/Rh for the EHR-M3; and 34 kV Rh/Ag for the Pristina. Two groups were identified in MTF analysis, and the group composed of Clarity, Opdima and Essential presented the highest MTF values. In NNPS analysis, three main groups were identified, in which the systems Crystal Nova and Essential presented lower and higher NNPS, respectively. Crystal Nova system also exhibited higher DQE values for low spatial frequencies, while Opdima and Clarity presented higher DQE values for medium to high spatial frequency. Agreement with data from literature indicates that the systems evaluated are operating under typical conditions. Evidence of improvement in detectors performance was found.

Noise Reduction for a Virtual Grid Using a Generative Adversarial Network in Breast X-ray Images.

In this study, we aimed to address the issue of noise amplification after scatter correction when using a virtual grid in breast X-ray images. To achieve this, we suggested an algorithm for estimating noise level and developed a noise reduction algorithm based on generative adversarial networks (GANs). Synthetic scatter in breast X-ray images were collected using Sizgraphy equipment and scatter correction was performed using dedicated software. After scatter correction, we determined the level of noise using noise-level function plots and trained a GAN using 42 noise combinations. Subsequently, we obtained the resulting images and quantitatively evaluated their quality by measuring the contrast-to-noise ratio (CNR), coefficient of variance (COV), and normalized noise-power spectrum (NNPS). The evaluation revealed an improvement in the CNR by approximately 2.80%, an enhancement in the COV by 12.50%, and an overall improvement in the NNPS across all frequency ranges. In conclusion, the application of our GAN-based noise reduction algorithm effectively reduced noise and demonstrated the acquisition of improved-quality breast X-ray images.

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.

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.

Study of the performance change in digital mammography systems depending on the total number of examinations

Digital mammography equipment should operate at a high-performance level for detecting breast cancer over the lifetime of the systems. This study investigates the performance of the Fujifilm Amulet Innovality full-field digital mammography system in relation to the number of exposures. The performance of twelve systems, from new and up to 17 000 examinations, was compared. The x-ray output, half-value layer (HVL), contrast-detail (C-D) detectability, contrast-to-noise ratio (CNR), mean glandular dose (MGD), signal transfer property (STP), pre-sampled modulation transfer function (MTF), normalized noise power spectra (NNPS), detective quantum efficiency (DQE) tests were performed to determine the performance change. The noise sources were also analyzed in the spatial domain. The x-ray output and HVL values at 28 kV with tungsten anode and rhodium filter were 15 μGy/mAs ± 1.0 (coefficient of variation (cov) = 7.0%) and 0.54 mmAl ± 0.008 (cov = 1.5%), respectively. The average MGDs for 60 mm equivalent breast to reach the achievable image quality level for 0.1 mm and 0.25 mm detail diameters of circular discs on the CDMAM 3.4 phantom image were 1.17 mGy ± 0.13 (cov = 11%) and 1.40 mGy ± 0.09 (cov = 6%), respectively. The average MGD for 53 mm equivalent breast was 1.08 mGy ± 0.14 (cov = 13%) at dose setting Normal in automatic exposure control (AEC) mode. All tested devices demonstrated good linearity with R2 ≥ 0.999 in the STP curves. The average MTF at 5.0 mm−1 spatial frequency was 0.66 ± 0.007 (cov = 1.0%). The average NNPS was 2.38 × 10−6 mm2 ± 2.13 × 10−7 (cov = 9.0%) at 5.0 mm−1. The average DQE value at 5.0 mm−1 was 0.33 ± 0.02 (cov = 5.0%), and the mean peak DQE was 0.66 ± 0.03 (cov = 5.0%). The mean power coefficient (b), determined from the power relationship between linearised standard deviation and detector dose while analyzing noise sources, was 0.49 ± 0.007 (cov = 1.4%). There was no gradual change in the x-ray tube and detector performance by the number of exposures, and taking up to 68 000 images did not decrease the quality of the systems.

Computational models of direct and indirect X-ray breast imaging detectors for in silico trials.

To facilitate in silico studies that investigate digital mammography (DM) and breast tomosynthesis (DBT), models replicating the variety in imaging performance of the DM and DBT systems, observed across manufacturers areneeded. The main purpose of this work is to develop generic physics models for direct and indirect detector technology used in commercially available systems, with the goal of making them available open source to manufacturers to further tweak and develop the exact in silico replicas of theirsystems. We recently reported on an in silico version of the SIEMENS Mammomat Inspiration DM/DBT system using an open-source GPU-accelerated Monte Carlo x-ray imaging simulation code (MC-GPU). We build on the previous version of the MC-GPU codes to mimic the imaging performances of two other Food and Drug Administration (FDA)-approved DM/DBT systems, such as Hologic Selenia Dimensions (HSD) and the General Electric Senographe Pristina (GSP) systems. In this work, we developed a hybrid technique to model the optical spread and signal crosstalk observed in the GSP and HSD systems. MC simulations are used to track each x-ray photon till its first interaction within the x-ray detector. On the other hand, the signal spread in the x-ray detectors is modeled using previously developed analytical equations. This approach allows us to preserve the modeling accuracy offered by MC methods in the patient body, while speeding up secondary carrier transport (either electron-hole pairs or optical photons) using analytical equationsin the detector. The analytical optical spread model for the indirect detector includes the depth-dependent spread and collection of optical photons and relies on a pre-computed set of point response functions that describe the optical spread as a function of depth. To understand the capabilities of the computational x-ray detector models, we compared image quality metrics like modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), simulated with our models against measured data. Please note that the purpose of these comparisons with measured data would be to gauge if the model developed as part of this work could replicate commercially used direct and indirect technology in general and not to achieve perfect fits with measureddata. We found that the simulated image quality metrics such as MTF, NNPS, and DQE were in reasonable agreement with experimental data. To demonstrate the imaging performance of the three DM/DBT systems, we integrated the detector models with the VICTRE pipeline and simulated DM images of a fatty breast model containing a spiculated mass and a calcium oxalate cluster. In general, we found that the images generated using the indirect model appeared more blurred with a different noise texture and contrast as compared to the systems with directdetectors. We have presented computational models of three commercially available FDA-approved DM/DBT systems, which implement both direct and indirect detector technology. The updated versions of the MC-GPU codes that can be used to replicate three systems are available in open source format throughGitHub.

Fabrication and application of customized breast phantom for MMWF noise reduction algorithm in digital mammography: An experimental study

Quantitative analysis in mammography is commonly carried out using a customized breast phantom. Noise reduction algorithms such as Wiener, median, and median modified Wiener filter (MMWF) with 3×3, 5×5, 7×7, and 9×9 mask sizes are applied to digital medical images because the digital images contain noise distributions such as Gaussian noise. The purpose of this study was to validate a customized breast phantom consisting of three positions for the inner structure (Condition A: 0.5 cm; condition B: 2.0 cm, condition C: 3.0 cm from the top surface) by applying the noise reduction algorithms listed above. The acquired images were evaluated using signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and normalized noise power spectrum (NNPS) parameters. When comparing conditions A, B and C, the SNR results using condition A were 1.2 and 1.3 times better, the CNR results were 1.9 and 3.3 times better, and the NNPS results were 1.2 and 1.3 times better than for conditions B and C, respectively. The application of algorithms was useful for the reduction of noise distribution; in particular, the MMWF algorithm with a 9×9 mask size presented the best performance in terms of SNR, CNR, and NNPS results. In conclusion, we confirmed that the location of the breast lesion can affect the image quality under the same scan conditions and that noise reduction algorithms are essential processes to improve image quality.

Characterization of digital systems used in medical X-ray imaging

The physical characteristics of two computed radiography (CR) systems, Carestream EHR-M3 and Carestream GP-2 (used in mammography and general radiography, respectively), were assessed at the standard beam conditions RQA-M2 and RQA-5, in the ranges of 9.5–800 μGy and 2.5–70 μGy, respectively. Objective criteria such as response function, modulation transfer function (MTF), normalized noise power spectrum (NNPS) and detective quantum efficiency (DQE) were employed for this evaluation. A careful image system noise analysis through component decomposition was performed in order to determine the quantum limited exposure range for each system. Both CR systems showed a logarithmic response in the tested air kerma range (R2 > 0.99). Spatial frequencies for 50% and 10% MTF were 2.0 mm−1 and 4.9 mm−1 for EHR-M3 mammography system and 1.1 mm−1 and 3.5 mm−1 for general radiography system GP-2. The mammography system EHR-M3 was quantum limited for the entire air kerma range evaluated, while GP-2 general radiography system was quantum noise limited for a range of 2.5–30 μGy. NNPS increased as kerma decreased for both systems. DQE increased with decreasing kerma for both systems. A quantitative technical characterization of digital systems was achieved for a variety of air kerma values, in the mammography and general radiography energy ranges.

Development of an algorithm to convert mammographic images to appear as if acquired with different technique factors.

Purpose: We set out a fully developed algorithm for adapting mammography images to appear as if acquired using different technique factors by changing the signal and noise within the images. The algorithm accounts for difference between the absorption by the object being imaged and the imaging system. Approach: Images were acquired using a Hologic Selenia Dimensions x-ray unit for the validation, of three thicknesses of polymethyl methacrylate (PMMA) blocks with or without different thicknesses of PMMA contrast objects acquired for a range of technique factors. One set of images was then adapted to appear the same as a target image acquired with a higher or lower tube voltage and/or a different anode/filter combination. The average linearized pixel value, normalized noise power spectra (NNPS), and standard deviation of the flat field images and the contrast-to-noise ratio (CNR) of the contrast object images were calculated for the simulated and target images. A simulation study tested the algorithm on images created using a voxel breast phantom at different technique factors and the images compared using local signal level, variance, and power spectra. Results: The average pixel value, NNPS, and standard deviation for the simulated and target images were found to be within 9%. The CNRs of the simulated and target images were found to be within 5% of each other. The differences between the target and simulated images of the voxel phantom were similar to those of the natural variability. Conclusions: We demonstrated that images can be successfully adapted to appear as if acquired using different technique factors. Using this conversion algorithm, it may be possible to examine the effect of tube voltage and anode/filter combination on cancer detection using clinical images.

Comparison of quantitative imaging characteristics between a new, larger-FOV 1000 fps high-speed angiographic (HSA) photon-counting detector (Aries) with a smaller HSA detector (Actaeon).

High Speed Angiography (HSA) requires imaging detectors with both high-temporal and high-spatial resolution. Both the Aries and Acteon detectors by Direct Conversion (Stockholm, Sweden) are CdTe direct photon-counting detectors (PCD) that have acquisition frame rates of up to 1000-fps and a 100-micrometer pixel pitch; however, the new Aries detector offers a larger field of view (512 × 768 pixels) compared to the smaller Actaeon detector (256 × 256 pixels). An expanded field of view is required for imaging of larger vasculature, thus the Aries offers this advantage. Evaluations were performed of both detectors under Anti-Coincidence Circuitry (ACC-ON) mode, which corrects for charge sharing between pixels. Initial evaluations of instrumentation noise and detector energy-threshold calibration using Am-241 gamma spectroscopy were performed for the new Aries detector. Linearity was also evaluated for the Aries for each of the 12 individual modules that compose the detector field to check for homogeneity in response to exposure throughout the detector. Finally, Normalized Noise Power Spectrum (NNPS), Modulation Transfer Function (MTF) and Detective Quantum Efficiency (DQE) were then compared between the Aries and Actaeon detectors at two different exposures and detector energy thresholds. The detectors are linear up to approximately 1000 μR and have no instrumentation noise above a threshold of 15 keV. As expected, the MTF's and DQE's are similar between the Aries and Actaeon detectors, and there are thus no tradeoff's in image quality to achieve the larger FOV.

Performance analysis of improved hybrid median filter applied to X-ray computed tomography images obtained with high-resolution photon-counting CZT detector: A pilot study

We evaluated the performance of an improved hybrid median filter (IHMF) applied to X-ray computed tomography (CT) images obtained using a high-resolution photon-counting cadmium zinc telluride (CZT) detector. To study how the proposed approach improves the image quality, we measured the noise levels and the overall CT-image quality. We established a CZT imaging system with a detector length of 5.12 cm and thickness of 0.3 cm and acquired phantom images. To evaluate the efficacy of the proposed filter, we first modeled two conventional median filters. Subsequently, we were able to achieve a normalized noise power spectrum result of ∼10−8 mm2, and furthermore, the proposed method improved the contrast-to-noise ratio by a factor of ∼1.51 and the coefficient of variation by 1.55 relative to the counterpart values of the no-filter image. In addition, the IHMF exhibited the best performance among the three filters considered as regards the peak signal-to-noise ratio and no-reference-based image-quality evaluation parameters. Thus, our results demonstrate that the IHMF approach provides a superior image performance over conventional median filtering methods when applied to actual CZT X-ray CT images.

Is the image quality of conventional chest radiography obtained from a two-layer flat panel detector affected by the internal structure of the detector?

PurposeRecently developed and commercialized dual-layer flat panel detectors (DL-FPDs) with two indirect scintillators are capable of acquiring dual-energy X-ray images. However, in clinical practice, they are utilized to perform conventional radiography using diagnostic X-rays with a wide energy spectrum. The two layers of the DL-FPD may affect the obtained image quality, even when only using one layer for conventional image acquisition, and these effects are yet to be substantiated. Therefore, in this study, we quantitatively evaluated the image quality of a conventional chest radiography using DL-FPD and visually verified the characteristics of the chest anthropomorphic phantom images. MethodsThe physical characteristics of the system were evaluated using the pre-sampled modulation transfer function (MTF), normalized noise power spectrum (NNPS), and detective quantum efficiency (DQE), for beam quality RQA 7 and RQA 9. In addition, the subjective visibility of the anthropomorphic chest phantom and simple objects images were compared with those of a conventional single-layer flat-panel detector (SL-FPD). ResultsNo significant differences were found in the MTF between the SL-FPD and DL-FPD images. In addition, a higher DQE was observed at some exposure doses and in the high spatial frequency regions wherein NNPSs were lower for DL-FPD than for SL-FPD. Furthermore, no significant differences were found in the subjective visibility of the chest phantoms in each system. ConclusionsWe concluded that the image quality of the conventional radiography acquired with DL-FPD is comparable to or better than that of the SL-FPD.

Evaluation of Noise Properties at Nonuniformity Area and Resolution Properties of CT Image Using Iterative Reconstruction Method

The purpose of this study was to investigate the resolution property and the noise properties at the nonuniformity area in the slice plane of iterative reconstruction (IR)-CT image. CT images of a phantom with nonuniformity areas including multiple contrast (medium, high, and ultra-high contrast) signals were acquired at various scan dose conditions and reconstructed with different iterative intensity levels. The noise properties at the nonuniformity and the uniformity areas were evaluated by measuring normalized noise power spectra (nNPSs) using subtracted images from sequential scanning data under the same scan conditions. We investigated the relationship between the noise properties and the resolution properties evaluated by measuring task transfer function (TTF) using multiple contrast signals before the subtraction. There was a correlation between the nNPS at the nonuniformity area and the TTF because the nNPS values at high spatial frequency were increased with superior TTF (higher dose, mild iterative intensity, and higher contrast level). The differences in the high spatial frequency component of the nNPSs among each task were decreased with the inferior TTF tasks. We conclude that the noise properties in the slice plane at the nonuniformity area and resolution properties of the IR-CT image were correlated similar to image quality properties of the linear imaging system due to the dependence of the nNPSs curve on the TTF value under each task.

MAMMO_QC: Free software for quality control (QC) analysis in digital mammography and digital breast tomosynthesis compliant with the European guidelines and EUREF/EFOMP protocols

Quality Control (QC) tests in mammography are very important, since mammograms have been used as a population-based screening test for more than 30 years and QCs lead to better image quality and radiation safety for patients. European guidelines, EUREF and EFOMP protocols provide comprehensive QC guidelines for digital mammography (DM) and digital breast tomosynthesis (DBT) units, respectively. We developed a novel, fast, free and platform independent software (named MAMMO_QC) for QC performance tests in DM and tomosynthesis, based on the aforementioned guidelines. MAMMO_QC consists of a series of ImageJ plugins for DM and DBT. It does not require any programming knowledge and can be used to evaluate several performance parameters, such as pre-sampled modulation transfer function (pMTF), normalised noise power spectrum (NNPS), detective quantum efficiency (DQE), contrast-detail analysis based on the CDMAM 3.4 and 4.0 test tools, homogeneity and artefacts, automatic exposure control (AEC) performance. The user can use MAMMO_QC for acceptance, commissioning and routine QC performance analysis based on the European guidelines. We validated our results against well-established software products used in mammography and DBT (i.e., COQ, OBJ_IQ_reduced and Artinis CDMAM Analyzer). All the average relative differences were within 5.5%, and several years of usage and testing allows us to consider MAMMO_QC as an accurate and reliable tool for QC on DM and DBT systems. Our developed software for DM and DBT computes almost all the parameters stated in the European, EUREF and EFOMP guidelines. To the best of our knowledge, no such software has been developed so far.

Quantitative Image Quality Metrics of the Low-Dose 2D/3D Slot Scanner Compared to Two Conventional Digital Radiography X-ray Imaging Systems.

The aim of this study was to determine the quantitative image quality metrics of the low-dose 2D/3D EOS slot scanner X-ray imaging system (LDSS) compared with conventional digital radiography (DR) X-ray imaging systems. The effective detective quantum efficiency (eDQE) and effective noise quantum equivalent (eNEQ) were measured using chest and knee protocols. Methods: A Nationwide Evaluation of X-ray Trends (NEXT) of a chest adult phantom and a PolyMethylmethacrylate (PMMA) phantom were used for the chest and knee protocols, respectively. Quantitative image quality metrics, including effective normalised noise power spectrum (eNNPS), effective modulation transfer function (eMTF), eDQE and eNEQ of the LDSS and DR imaging systems were assessed and compared. Results: In the chest acquisition, the LDSS imaging system achieved significantly higher eNEQ and eDQE than the DR imaging systems at lower and higher spatial frequencies (0.001 ≤ p ≤ 0.044). For the knee acquisition, the LDSS imaging system also achieved significantly higher eNEQ and eDQE than the DR imaging systems at lower and higher spatial frequencies (0.001 ≤ p ≤ 0.002). However, there was no significant difference in eNEQ and eDQE between DR systems 1 and 2 at lower and higher spatial frequencies (0.10 < p < 1.00) for either chest or knee protocols. Conclusion: The LDSS imaging system performed well compared to the DR systems. Thus, we have demonstrated that the LDSS imaging system has the potential to be used for clinical diagnostic purposes.

Image texture, low contrast liver lesion detectability and impact on dose: Deep learning algorithm compared to partial model-based iterative reconstruction

ObjectivesTo compare deep learning (True Fidelity, TF) and partial model based Iterative Reconstruction (ASiR-V) algorithm for image texture, low contrast lesion detectability and potential dose reduction. MethodsAnthropomorphic phantoms (mimicking non-overweight and overweight patient), containing lesions of 6 mm in diameter with 20HU contrast, were scanned at five different dose levels (2,6,10,15,20 mGy) on a CT system, using clinical routine protocols for liver lesion detection. Images were reconstructed using ASiR-V 0% (surrogate for FBP), 60 % and TF at low, medium and high strength. Noise texture was characterized by computing a normalized Noise Power Spectrum filtered by an eye filter. The similarity against FBP texture was evaluated using peak frequency difference (PFD) and root mean square deviation (RMSD). Low contrast detectability was assessed using a channelized Hotelling observer and the area under the ROC curve (AUC) was used as figure of merit. Potential dose reduction was calculated to obtain the same AUC for TF and ASiR-V. ResultsFBP-like noise texture was more preserved with TF (PFD from -0.043mm-1 to -0.09mm-1, RMSD from 0.12mm-1 to 0.21mm-1) than with ASiR-V (PFD equal to 0.12 mm-1, RMSD equal to 0.53mm-1), resulting in a sharper image. AUC was always higher with TF than ASIR-V. In average, TF compared to ASiR-V, enabled a radiation dose reduction potential of 7%, 25 % and 33 % for low, medium and high strength respectively. ConclusionCompared to ASIR-V, TF at high strength does not impact noise texture and maintains low contrast liver lesions detectability at significant lower dose.

Examinations for creating an image of unacquired dose from the images of two types of dose in digital radiography.

Digital radiography (DR) is grayscale adjustable and it can be unclear whether an acquired DR image is captured with the minimum radiation dose required. It is necessary to make an image of the amount of noise when taken at a lower dose than the acquired image, without increased exposure. To examine whether an image of unacquired dose can be created from two types of dose DR images acquired using a phantom. To create an additive image from two images of different doses, the pixel value of one image is multiplied by a coefficient and added to the other. The normalized noise power spectra (NNPS) of the normal image and the additive image with the same signal-to-noise ratio (SNR) are compared. The image noise of the unacquired doses is estimated from the graph changes of the pixel values and standard deviations of two images. The error between the SNR of the image obtained by changing the dose and the estimated SNR is measured. We propose a multiplication coefficient calculation formula that theoretically adjusts the additive image to the target SNR. The SNR error of the image created based on this formula is measured. The NNPS curves of the additive and normal images show a difference on the high frequency side. According to the statistics considering the preset of mAs value, there is no significant difference at 85%. The SNR estimation error is approximately 1%. The SNR error of the additive image created based on the formula is approximately 5%. The noise of the image of unacquired dose can be estimated, and the additive image adjusted to this value can be considered equivalent to the image taken at the actual dose.

Frequency-dependent optimal weighting approach for megavoltage multilayer imagers

Multi-layer imaging (MLI) devices improve the detective quantum efficiency (DQE) while maintaining the spatial resolution of conventional mega-voltage (MV) x-ray detectors for applications in radiotherapy. To date, only MLIs with identical detector layers have been explored. However, it may be possible to instead use different scintillation materials in each layer to improve the final image quality. To this end, we developed and validated a method for optimally combining the individual images from each layer of MLI devices that are built with heterogeneous layers. Two configurations were modeled within the GATE Monte Carlo package by stacking different layers of a terbium doped gadolinium oxysulfide Gd2O2S:Tb (GOS) phosphor and a LKH-5 glass scintillator. Detector response was characterized in terms of the modulation transfer function (MTF), normalized noise power spectrum (NNPS) and DQE. Spatial frequency-dependent weighting factors were then analytically derived for each layer such that the total DQE of the summed combination image would be maximized across all spatial modes. The final image is obtained as the weighted sum of the sub-images from each layer. Optimal weighting factors that maximize the DQE were found to be the quotient of MTF and NNPS of each layer in the heterogeneous MLI detector. Results validated the improvement of the DQE across the entire frequency domain. For the LKH-5 slab configuration, DQE(0) increases between 2%–3% (absolute), while the corresponding improvement for the LKH-5 pixelated configuration was 7%. The performance of the weighting method was quantitatively evaluated with respect to spatial resolution, contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of simulated planar images of phantoms at 2.5 and 6 MV. The line pair phantom acquisition exhibited a twofold increase in CNR and SNR, however MTF was degraded at spatial frequencies greater than 0.2 lp mm−1. For the Las Vegas phantom, the weighting improved the CNR by around 30% depending on the contrast region while the SNR values are higher by a factor of 2.5. These results indicate that the imaging performance of MLI systems can be enhanced using the proposed frequency-dependent weighting scheme. The CNR and SNR of the weighted combined image are improved across all spatial scales independent of the detector combination or photon beam energy.

On the Response of a Micro Non-Destructive Testing X-ray Detector.

Certain imaging performance metrics are examined for a state-of-the-art 20 μm pixel pitch CMOS sensor (RadEye HR), coupled to a Gd2O2S:Tb scintillator screen. The signal transfer property (STP), the modulation transfer function (MTF), the normalized noise power spectrum (NNPS) and the detective quantum efficiency (DQE) were estimated according to the IEC 62220-1-1:2015 standard. The detector exhibits excellent linearity (coefficient of determination of the STP linear regression fit, R2 was 0.9978), while its DQE peaks at 33% and reaches 10% at a spatial frequency of 3 cycles/mm, for the measured with a Piranha RTI dosimeter (coefficient of variation CV = 0.03%) exposure value of 28.1 μGy DAK (detector Air Kerma). The resolution capabilities of the X-ray detector under investigation were compared to other commercial CMOS sensors, and were found in every case higher, except from the previous RadEye HR model (CMOS—Gd2O2S:Tb screen pair with 22.5 μm pixel pitch) version which had slightly better MTF. The present digital imager is designed for industrial inspection applications, nonetheless its applicability to medical imaging, as well as dual-energy is considered and certain approaches are discussed in this respect.