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Objective . To assess the performance of a new antiscatter grid design in interventional cardiology for image quality improvement and dose reduction using experimental measurements and Monte Carlo (MC) simulation. Approach. Experimental measurements were performed on an angiography system, using a multi-layered tissue simulating composite phantom made from of poly(methyl methacrylate), aluminium and expanded polystyrene (2/0.2/0.7 cm). The total phantom thickness ranged from 20.3 cm to 40.6 cm. Four conditions were compared; (A) 105 cm source-image receptor distance (SID) without grid, ( B i ) 105 cm SID with grid ratio ( r ) and strip density ( N ) ( r 15 N 80), ( B ii ) 120 cm SID without grid, and (B iii ) 120 cm SID with high ratio grid ( r ), defined by the signal-to-noise ratio, was compared from the N 80). The system efficiency ( η ), defined by the signal-to-noise ratio, was compared from the B conditions against case A . These conditions were also simulated with MC techniques, allowing additional phantom compositions to be explored. Weighted image quality improvement factor ( η w ( u )) was studied experimentally at a specific spatial frequency due to the SID change. Images were simulated with an anthropomorphic chest phantom for the different conditions, and the system efficiency was compared for the different anatomical regions. Main results. Good agreement was found between the η and η w ( u ) methods using both measured and simulated data, with average relative differences between 2%-11%. Case B iii provided higher η values compared to A , and B i for thicknesses larger than 20.3 cm. In addition, case B iii also provided higher η values for high attenuating areas in the anthropomorphic phantom, such as behind the spine. Significance. The new antiscatter grid design provided higher system efficiency compared to the standard grid for the parameters explored in this work., (© 2024 Institute of Physics and Engineering in Medicine.)

Purpose: Evaluating the time-of-flight (TOF) resolution improvement that could be obtained using an easy crystal block modification which enables depth of interaction (DOI) assessment and simplifies the detector assembling process., Method: A fast optical Monte Carlo (MC) code was developed. The code was evaluated versus measurements of the energy resolution, number of detected scintillation photons and TOF resolution (TOFr) reported for different crystal photodetector setups. Then, MC simulations were performed for a modified crystal block section of 8 × 8 mm 2 in which two partial saw cuts allow light sharing between four detector pixels with a strong dependence on the DOI., Results: Relative differences between MC simulations and reported measurements were always below 10% for any quantities. The simulations showed that the best TOFr was obtained by leaving the partial saw cuts empty. This feature results from the fact that for a slant angle lower than 56 degrees, the scintillation photons undergo a lossless total reflection at the L[Y]SO → air boundary, which is hardly achievable using a reflector material. According to the simulations, this approach allows a TOFr improvement from 163 ps to 90 ps full width at half-maximum using a 22 mm thick LSO 0.2%Ca:Ce crystal coupled to a FBK-NUV-HD silicon photomultiplier., Conclusion: Sub-100 ps TOFr using thick LSO crystal appears achievable using this simple crystal block modification. The method reduces by a factor of 4 the number of crystal pixels to be covered by a reflective material and afterwards joined together. As clinical positron emission tomography contains about 60 000 crystal pixels, this benefit would reduce the assembling cost.

The primary cone-beam computed tomography (CBCT) imaging beam scatters inside the patient and produces a contaminating photon fluence that is registered by the detector. Scattered photons cause artifacts in the image reconstruction, and are partially responsible for the inferior image quality compared to diagnostic fan-beam CT. In this work, a deep convolutional autoencoder (DCAE) and projection-based scatter removal algorithm were constructed for the ImagingRing TM system on rails (IRr), which allows for non-isocentric acquisitions around virtual rotation centers with its independently rotatable source and detector arms. A Monte Carlo model was developed to simulate (i) a non-isocentric training dataset of ≈1200 projection pairs (primary + scatter) from 27 digital head-and-neck cancer patients around five different virtual rotation centers (DCAE NONISO ), and (ii) an isocentric dataset existing of ≈1200 projection pairs around the physical rotation center (DCAE ISO ). The scatter removal performance of both DCAE networks was investigated in two digital anthropomorphic phantom simulations and due to superior performance only the DCAE NONISO was applied on eight real patient acquisitions. Measures for the quantitative error, the signal-to-noise ratio, and the similarity were evaluated for two simulated digital head-and-neck patients, and the contrast-to-noise ratio (CNR) was investigated between muscle and adipose tissue in the real patient image reconstructions. Image quality metrics were compared between the uncorrected data, the currently implemented heuristic scatter correction data, and the DCAE corrected image reconstruction. The DCAE NONISO corrected image reconstructions of two digital patient simulations showed superior image quality metrics compared to the uncorrected and corrected image reconstructions using a heuristic scatter removal. The proposed DCAE NONISO scatter correction in this study was successfully demonstrated in real non-isocentric patient CBCT acquisitions and achieved statistically significant higher CNRs compared to the uncorrected or the heuristic corrected image data. This paper presents for the first time a projection-based scatter removal algorithm for isocentric and non-isocentric CBCT imaging using a deep convolutional autoencoder trained on Monte Carlo composed datasets. The algorithm was successfully applied to real patient data.

Purpose: To find comprehensive equations for the frequency-dependent MTF and DQE of photon counting detectors including the effect that the combination of crosstalk with an energy threshold is changing the pixel sensitivity profile and to compare the results with measurements., Methods: The framework of probability-generating functions (PGF) is used to find a simple method to derive the MTF and the DQE directly from a Monte-Carlo model of the detection process., Results: In combination with realistic model parameters for the detector, the method is used to predict the MTF and the DQE for different pixel sizes and thresholds. Particularly for small pixels, the modification of the sensitivity profile due to crosstalk substantially affects the frequency dependence of both quantities., Conclusion: The phenomenon of the pixel sensitivity profile, i.e. the fact that the choice of the threshold is affecting the detector sharpness, may play a substantial role in exploiting the full potential of photon counting detectors. The model compares well with measurements: with only two model parameters, the model can predict the MTF(f) and the DQE(f) for a wide range of thresholds.

Much research effort is being made to increase the sensitivity and improve the imaging performance of positron emission tomography (PET) scanners. Conventionally, sensitivity can be increased by increasing the number of detector rings in the axial direction (but at high cost) or reducing the diameter of the scanner (with the disadvantages of reducing the space for patients and degrading the spatial resolution due to the parallax error). In this study, we proposed a PET scanner with a truncated ring and an array of detectors that can be arranged in a straight line below the bed. We called this system 'D-PET' as it resembles the letter 'D' when it is rotated by 90° in the counterclockwise direction. The basic design idea was to cut the unused space under the patient's bed; this area is usually not in use in clinical diagnosis. We conducted Monte Carlo simulations of the D-PET scanner and compared its performance with a cylindrical PET scanner. The scanners were constructed from 4-layer depth-of-interaction detectors which consisted of a 16  ×  16  ×  4 LYSO crystal array with dimensions of 2.85  ×  2.85  ×  5 mm 3 . The results showed that the D-PET had an increase in sensitivity and peak-NECR of 30% and 18%, respectively. The D-PET had low noise in the reconstructed images throughout the field-of-view compared to the cylindrical PET. These were achieved while keeping sufficient space for the patient, and also without a severe effect on the spatial resolution. Furthermore, the number of detectors (and hence the cost) of the D-PET scanner was reduced by 12% compared to the cylindrical PET scanner.

Computed tomography (CT) has been used for a variety of applications, two of which include diagnostic imaging and attenuation correction for PET or SPECT imaging. Ideally, the x-ray tube spectrum should be optimized for the specific application to minimize the patient radiation dose while still providing the necessary information. In this study, we proposed a projection-based analytic approach for the analysis of contrast, noise, and bias. Dose normalized contrast to noise ratio (CNRD), inverse noise normalized by dose (IND) and bias are used as evaluation metrics to determine the optimal x-ray spectrum. Our simulation investigated the dose efficiency of the x-ray spectrum ranging from 40 kVp to 200 kVp. Water cylinders with diameters of 15 cm, 24 cm, and 35 cm were used in the simulation to cover a variety of patient sizes. The effects of electronic noise and pre-patient copper filtration were also evaluated. A customized 24 cm CTDI-like phantom with 13 mm diameter inserts filled with iodine (10 mg ml -1 ), tantalum (10 mg ml -1 ), water, and PMMA was measured with both standard (1.5 mGy) and ultra-low (0.2 mGy) dose to verify the simulation results at tube voltages of 80, 100, 120, and 140 kVp. For contrast-enhanced diagnostic imaging, the simulation results indicated that for high dose without filtration, the optimal kVp for water contrast is approximately 100 kVp for a 15 cm water cylinder. However, the 60 kVp spectrum produces the highest CNRD for bone and iodine. The optimal kVp for tantalum has two selections: approximately 50 and 100 kVp. The kVp that maximizes CNRD increases when the object size increases. The trend in the CTDI phantom measurements agrees with the simulation results, which also agrees with previous studies. Copper filtration improved the dose efficiency for water and tantalum, but reduced the iodine and bone dose efficiency in a clinically-relevant range (70-140 kVp). Our study also shows that for CT-based attenuation correction applications for PET or SPECT, a higher-kVp spectrum with copper filtration is preferable. This method is developed based on filter back projection and does not require image reconstruction or Monte Carlo dose estimates; thus, it could potentially be used for patient-specific and task-based on-the-fly protocol optimization.

Geant4 application for tomographic emission (GATE), a Monte-Carlo simulation platform, has previously been used for optimizing tomoscintigraphic images recorded with scintillation Anger cameras but not with the new-generation heart-centric cadmium-zinc-telluride (CZT) cameras. Using the GATE platform, this study aimed at simulating the SPECT recordings from one of these new CZT cameras and to assess this simulation by direct comparison between simulated and actual recorded data, ranging from point sources to human images. Geometry and movement of detectors, as well as their respective energy responses, were modeled for the CZT 'D.SPECT' camera in the GATE platform. Both simulated and actual recorded data were obtained from: (1) point and linear sources of (99m)Tc for compared assessments of detection sensitivity and spatial resolution, (2) a cardiac insert filled with a (99m)Tc solution for compared assessments of contrast-to-noise ratio and sharpness of myocardial borders and (3) in a patient with myocardial infarction using segmented cardiac magnetic resonance imaging images. Most of the data from the simulated images exhibited high concordance with the results of actual images with relative differences of only: (1) 0.5% for detection sensitivity, (2) 6.7% for spatial resolution, (3) 2.6% for contrast-to-noise ratio and 5.0% for sharpness index on the cardiac insert placed in a diffusing environment. There was also good concordance between actual and simulated gated-SPECT patient images for the delineation of the myocardial infarction area, although the quality of the simulated images was clearly superior with increases around 50% for both contrast-to-noise ratio and sharpness index. SPECT recordings from a new heart-centric CZT camera can be simulated with the GATE software with high concordance relative to the actual physical properties of this camera. These simulations may be conducted up to the stage of human SPECT-images even if further refinement is needed in this setting.

The aim of this study is to investigate the impact on image quality of using monochromatic beams for lower dose breast tomosynthesis (BT). For this purpose, modeling and simulation of BT and mammography imaging processes have been performed using two x-ray beams: one at 28 kVp and a monochromatic one at 19 keV at different entrance surface air kerma ranging between 0.16 and 5.5 mGy. Two 4 cm thick computational breast models, in a compressed state, were used: one simple homogeneous and one heterogeneous based on CT breast images, with compositions of 50% glandular-50% adipose and 40% glandular-60% adipose tissues by weight, respectively. Modeled lesions, representing masses and calcifications, were inserted within these breast phantoms. X-ray transport in the breast models was simulated with previously developed and validated Monte Carlo application. Results showed that, for the same incident photon fluence, the use of the monochromatic beam in BT resulted in higher image quality compared to the one using polychromatic acquisition, especially in terms of contrast. For the homogenous phantom, the improvement ranged between 15% and 22% for calcifications and masses, respectively, while for the heterogeneous one this improvement was in the order of 33% for the masses and 17% for the calcifications. For different exposures, comparable image quality in terms of signal-difference-to-noise ratio and higher contrast for all features was obtained when using a monochromatic 19 keV beam at a lower mean glandular dose, compared to the polychromatic one. Monochromatic images also provide better detail and, in combination with BT, can lead to substantial improvement in visualization of features, and particularly better edge detection of low-contrast masses.

In-beam positron emission tomography (PET) can enable visualization of an irradiated field using positron emitters (β+ decay). In particle therapies, many kinds of secondary particles are produced by nuclear interactions, which affect PET imaging. Our purpose in this work was to evaluate effects of secondary particles on in-beam PET imaging using the Monte Carlo simulation code, Geant4, by reproducing an experiment with a small OpenPET prototype in which a PMMA phantom was irradiated by a (11)C beam. The number of incident particles to the detectors and their spectra, background coincidence for the PET scan, and reconstructed images were evaluated for three periods, spill-time (beam irradiation), pause-time (accelerating the particles) and beam-off time (duration after the final spill). For spill-time, we tested a background reduction technique in which coincidence events correlated with the accelerator radiofrequency were discarded (RF gated) that has been proposed in the literature. Also, background generation processes were identified. For spill-time, most background coincidences were caused by prompt gamma rays, and only 1.4% of the total coincidences generated β+ signals. Differently, for pause-time and beam-off time, more than 75% of the total coincidence events were signals. Using these coincidence events, we failed to reconstruct images during the spill-time, but we obtained successful reconstructions for the pause-time and beam-off time, which was consistent with the experimental results. From the simulation, we found that the absence of materials in the beam line and using the RF gated technique improved the signal-to-noise ratio for the spill-time. From an additional simulation with range shifter-less irradiation and the RF gated technique, we showed the feasibility of image reconstruction during the spill-time.

Monte Carlo simulations of emission tomography have proven useful to assist detector design and optimize acquisition and processing protocols. The more realistic the simulations, the more straightforward the extrapolation of conclusions to clinical situations. In emission tomography, accurate numerical models of tomographs have been described and well validated under specific operating conditions (collimator, radionuclide, acquisition parameters, count rates, etc). When using these models under these operating conditions, the realism of simulations mostly depends on the activity distribution used as an input for the simulations. It has been proposed to derive the input activity distribution directly from reconstructed clinical images, so as to properly model the heterogeneity of the activity distribution between and within organs. However, reconstructed patient images include noise and have limited spatial resolution. In this study, we analyse the properties of the simulated images as a function of the properties of the reconstructed images used to define the input activity distributions in (18)F-FDG PET and (131)I SPECT simulations. The propagation through the simulation/reconstruction process of the noise and spatial resolution in the input activity distribution was studied using simulations. We found that the noise properties of the images reconstructed from the simulated data were almost independent of the noise in the input activity distribution. The spatial resolution in the images reconstructed from the simulations was slightly poorer than that in the input activity distribution. However, using high-noise but high-resolution patient images as an input activity distribution yielded reconstructed images that could not be distinguished from clinical images. These findings were confirmed by simulated highly realistic (131)I SPECT and (18)F-FDG PET images from patient data. In conclusion, we demonstrated that (131)I SPECT and (18)F-FDG PET images indistinguishable from real scans can be simulated using activity maps with spatial resolution higher than that used in routine clinical applications.

Objective. This work proposes, for the first time, an image-based end-to-end self-normalization framework for positron emission tomography (PET) using conditional generative adversarial networks (cGANs). Approach. We evaluated different approaches by exploring each of the following three methodologies. First, we used images that were either unnormalized or corrected for geometric factors, which encompass all time-invariant factors, as input data types. Second, we set the input tensor shape as either a single axial slice (2D) or three contiguous axial slices (2.5D). Third, we chose either Pix2Pix or polarized self-attention (PSA) Pix2Pix, which we developed for this work, as a deep learning network. The targets for all approaches were the axial slices of images normalized using the direct normalization method. We performed Monte Carlo simulations of ten voxelized phantoms with the SimSET simulation tool and produced 26,000 pairs of axial image slices for training and testing. Main results. The results showed that 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the best performance among all the methods we tested. All approaches improved general image quality figures of merit peak signal to noise ratio (PSNR) and structural similarity index (SSIM) from ∼15 % to ∼55 %, and 2.5D PSA Pix2Pix showed the highest PSNR (28.074) and SSIM (0.921). Lesion detectability, measured with region of interest (ROI) PSNR, SSIM, normalized contrast recovery coefficient, and contrast-to-noise ratio, was generally improved for all approaches, and 2.5D PSA Pix2Pix trained with geometric-factors-corrected input images achieved the highest ROI PSNR (28.920) and SSIM (0.973). Significance. This study demonstrates the potential of an image-based end-to-end self-normalization framework using cGANs for improving PET image quality and lesion detectability without the need for separate normalization scans. [ABSTRACT FROM AUTHOR]

In this study, we investigated the capacity of various ion beams available for radiotherapy to produce high quality relative stopping power map acquired from energy-loss measurements. The image quality metrics chosen to compare the different ions were signal-to-noise ratio (SNR) as a function of dose and spatial resolution. Geant4 Monte Carlo simulations were performed for: hydrogen, helium, lithium, boron and carbon ion beams crossing a 20 cm diameter water phantom to determine SNR and spatial resolution. It has been found that protons possess a significantly larger SNR when compared with other ions at a fixed range (up to 36% higher than helium) due to the proton nuclear stability and low dose per primary. However, it also yields the lowest spatial resolution against all other ions, with a resolution lowered by a factor 4 compared to that of carbon imaging, for a beam with the same initial range. When comparing for a fixed spatial resolution of 10 lp cm−1, carbon ions produce the highest image quality metrics with proton ions producing the lowest. In conclusion, it has been found that no ion can maximize all image quality metrics simultaneously and that a choice must be made between spatial resolution, SNR, and dose. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Optical fibre backscatter reflectometry is an important technique for Structural Health Monitoring (SHM). In recent years, increasing the intensity of backscattered light in backscatter reflectometry has shown the advantage of improving the signal detection in shape sensing and temperature detection due to the increase of signal to noise ratio and this approach could potentially be used to improve the performance of an SHM system. Doping nanoparticles (NPs) is a method to increase the intensity of backscattered light in distributed fibre optic sensing. The increased intensity of light backscattered by the NPs needs to be investigated to design suitable optical sensing fibres with NPs for backscatter reflectometry. In this work NPs were added to refractive index matching liquid and tested with commercial NP suspensions experimentally between the tips of two optical fibres. An estimate of the intensity of backscattered light from the NPs in this structure was performed by simulation to give a better understanding of the expected levels of intensities of scattered light from NPs in this distributed fibre optic sensing configuration. We present analytical models based on Mie theory and the Monte Carlo Method. Simulated results are presented, for a broad bandwidth Gaussian spectra shape incident light with a central wavelength around 1550 nm, to match the experimental conditions in this work. The novelty is in developing this model for scattered light by NPs at optical fibre interfaces and the evaluation of the possibility of detection by the calculated scattered intensity levels. [ABSTRACT FROM AUTHOR]

In heavy-ion therapy, the stopping position of primary ions in tumours needs to be monitored for effective treatment and to prevent overdose exposure to normal tissues. Positron-emitting ion beams, such as 11C and 15O, have been suggested for range verification in heavy-ion therapy using in-beam positron emission tomography (PET) imaging, which offers the capability of visualizing the ion stopping position with a high signal-to-noise ratio. We have previously demonstrated the feasibility of in-beam PET imaging for the range verification of 11C and 15O ion beams and observed a slight shift between the beam stopping position and the dose peak position in simulations, depending on the initial beam energy spread. In this study, we focused on the experimental confirmation of the shift between the Bragg peak position and the position of the maximum detected positron-emitting fragments via a PET system for positron-emitting ion beams of 11C (210 MeV u−1) and 15O (312 MeV u−1) with momentum acceptances of 5% and 0.5%. For this purpose, we measured the depth doses and performed in-beam PET imaging using a polymethyl methacrylate (PMMA) phantom for both beams with different momentum acceptances. The shifts between the Bragg peak position and the PET peak position in an irradiated PMMA phantom for the 15O ion beams were 1.8 mm and 0.3 mm for momentum acceptances of 5% and 0.5%, respectively. The shifts between the positions of two peaks for the 11C ion beam were 2.1 mm and 0.1 mm for momentum acceptances of 5% and 0.5%, respectively. We observed larger shifts between the Bragg peak and the PET peak positions for a momentum acceptance of 5% for both beams, which is consistent with the simulation results reported in our previous study. The biological doses were also estimated from the calculated relative biological effectiveness (RBE) values using a modified microdosimetric kinetic model (mMKM) and Monte Carlo simulation. Beams with a momentum acceptance of 5% should be used with caution for therapeutic applications to avoid extra dose to normal tissues beyond the tumour when the dose distal fall-off is located beyond the treatment volume. [ABSTRACT FROM AUTHOR]

A number of B1 mapping methods have been introduced. A model to facilitate choice among these methods is valuable, as the performance of each technique is affected by a variety of factors, including acquisition signal-to-noise ratio (SNR). The Bloch-Siegert shift B1 mapping method has recently garnered significant interest. In this paper, we present a statistical model suitable for analysis of the Bloch-Siegert shift method. Unlike previously presented models, the analysis is valid in both low SNR and high SNR regimes. We present a detailed analysis of the performance of the Bloch-Siegert shift B1 mapping method across a broad range of acquisition scenarios, and compare it to two other B1 mapping techniques (the dual angle method and the phase sensitive method). Further validation of the model is presented through both Monte Carlo simulations and experimental results. The simulations and experimental results match the model well, lending confidence to its accuracy. Each technique is found to perform well with high acquisition SNR. However, our results suggest that the dual angle method is not reliable in low SNR environments. Furthermore, the phase sensitive method appears to outperform the Bloch- Siegert shift method in these low-SNR cases, although variations of the Bloch- Siegert method may be possible that improve its performance at low SNR. [ABSTRACT FROM AUTHOR]

Clinical single photon emission computed tomography (SPECT) equipped with pinhole collimators have a magnification factor that results in high spatial resolution images for small animal imaging. Using Monte Carlo simulations to model the acquisition process and the propagation of the photons from their point of emission to their detection point then integrating the model into an iterative reconstruction algorithm improves the signal-to-noise ratio, the contrast and the spatial resolution in the reconstructed images. However, pinhole SPECT systems are known to be very sensitive to geometrical misalignments. Geometrical misalignments are defined as the radial or axial shift of the collimator pinhole and/or twist and tilt of the detector heads and are introduced in the system each time the collimation device is changed (pinhole to parallel holes or vice versa). In this work, we present a flexible detector response function table (DRFT) design that takes into account the geometrical misalignments and avoids performing new Monte Carlo simulations for each exam in order to calculate a geometrical study-dependent system matrix. The utilization of the DRFT for the calculation of the system matrix speeds up its computation time by two orders of magnitude making it acceptable for preclinical and clinical applications. [ABSTRACT FROM AUTHOR]

This paper describes a novel multiobjective parameter optimization method based on a genetic algorithm (GA) for the design of a sixth-order continuous-time, force feedback band-pass sigma-delta modulator (BP-&Sgr;&Dgr;M) interface for the sense mode of a MEMS gyroscope. The design procedure starts by deriving a parameterized Simulink model of the BP-&Sgr;&Dgr;M gyroscope interface. The system parameters are then optimized by the GA. Consequently, the optimized design is tested for robustness by a Monte Carlo analysis to find a solution that is both optimal and robust. System level simulations result in a signal-to-noise ratio (SNR) larger than 90 dB in a bandwidth of 64 Hz with a 200° s-1 angular rate input signal; the noise floor is about -100 dBV Hz-1/2. The simulations are compared to measured data from a hardware implementation. For zero input rotation with the gyroscope operating at atmospheric pressure, the spectrum of the output bitstream shows an obvious band-pass noise shaping and a deep notch at the gyroscope resonant frequency. The noise floor of measured power spectral density (PSD) of the output bitstream agrees well with simulation of the optimized system level model. The bias stability, rate sensitivity and nonlinearity of the gyroscope controlled by an optimized BP-&Sgr;&Dgr;M closed-loop interface are 34.15° h-1, 22.3 mV °-1 s-1, 98 ppm, respectively. This compares to a simple open-loop interface for which the corresponding values are 89° h-1, 14.3 mV °-1 s-1, 7600 ppm, and a nonoptimized BP-&Sgr;&Dgr;M closed-loop interface with corresponding values of 60° h-1, 17 mV °-1 s-1, 200 ppm. [ABSTRACT FROM AUTHOR]

We investigated the feasibility of designing an Anger-logic PET detector module using large-area high-gain avalanche photodiodes (APDs) for a brain-dedicated PET/MRI system. Using Monte Carlo simulations, we systematically optimized the detector design with regard to the scintillation crystal, optical diffuser, surface treatment, layout of large-area APDs, and signal-to-noise ratio (SNR, defined as the 511 keV photopeak position divided by the standard deviation of noise floor in an energy spectrum) of the APD devices. A detector prototype was built comprising an 8 x 8 array of 2.75 x 3.00 x 20.0 mm3 LYSO (lutetium-yttrium-oxyorthosilicate) crystals and a 22.0 x 24.0 x 9.0 mm3 optical diffuser. From the four designs of the optical diffuser tested, two designs employing a slotted diffuser are able to resolve all 64 crystals within the block with good uniformity and peak-to-valley ratio. Good agreement was found between the simulation and experimental results. For the detector employing a slotted optical diffuser, the energy resolution of the global energy spectrum after normalization is 13.4 +- 0.4%. The energy resolution of individual crystals varies between 11.3 +- 0.3% and 17.3 +- 0.4%. The time resolution varies between 4.85 +- 0.04 (center crystal), 5.17 +- 0.06 (edge crystal), and 5.18 +- 0.07 ns (corner crystal). The generalized framework proposed in this work helps to guide the design of detector modules for selected PET system configurations, including scaling the design down to a preclinical PET system, scaling up to a whole-body clinical scanner, as well as replacing APDs with other novel photodetectors that have higher gain or SNR such as silicon photomultipliers. [ABSTRACT FROM AUTHOR]

We investigate the performance of different methodologies that measure the time lag between broad-line and continuum variations in reverberation mapping data using simulated light curves that probe a range of cadence, time baseline, and signal-to-noise ratio in the flux measurements. We compare three widely adopted lag-measuring methods: the interpolated cross-correlation function (ICCF), the z-transformed discrete correlation function (ZDCF), and the Markov chain Monte Carlo code JAVELIN, for mock data with qualities typical of multiobject spectroscopic reverberation mapping (MOS-RM) surveys that simultaneously monitor hundreds of quasars. We quantify the overall lag-detection efficiency, the rate of false detections, and the quality of lag measurements for each of these methods and under different survey designs (e.g., observing cadence and depth) using mock quasar light curves. Overall JAVELIN and ICCF outperform ZDCF in essentially all tests performed. Compared with ICCF, JAVELIN produces higher quality lag measurements, is capable of measuring more lags with timescales shorter than the observing cadence, is less susceptible to seasonal gaps and signal-to-noise ratio degradation in the light curves, and produces more accurate lag uncertainties. We measure the Hβ broad-line region size–luminosity (R–L) relation with each method using the simulated light curves to assess the impact of selection effects of the design of MOS-RM surveys. The slope of the R–L relation measured by JAVELIN is the least biased among the three methods and is consistent across different survey designs. These results demonstrate a clear preference for JAVELIN over the other two nonparametric methods for MOS-RM programs, particularly in the regime of limited light-curve quality as expected from most MOS-RM programs. [ABSTRACT FROM AUTHOR]

We have developed a novel method for fast image simulation of flat panel detectors, based on the photon energy deposition efficiency and the optical spread function (OSF). The proposed method, FastEPID, determines the photon detection using photon energy deposition and replaces particle transport within the detector with precalculated OSFs. The FastEPID results are validated against experimental measurement and conventional Monte Carlo simulation in terms of modulation transfer function (MTF), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), contrast, and relative difference of pixel value, obtained with a slanted slit image, Las Vegas phantom, and anthropomorphic pelvis phantom. Excellent agreement is observed between simulation and measurement in all cases. Without degrading image quality, the FastEPID method is capable of reducing simulation time up to a factor of 150. Multiple applications, such as imager design optimization for planar and volumetric imaging, are expected to benefit from the implementation of the FastEPID method. [ABSTRACT FROM AUTHOR]

The population analysis and estimation of merger rates of compact binaries is one of the important topics in gravitational wave astronomy. The primary ingredient in these analyses is the population-averaged sensitive volume. Typically, sensitive volume, of a given search to a given simulated source population, is estimated by drawing signals from the population model and adding them to the detector data as injections. Subsequently injections, which are simulated gravitational waveforms, are searched for by the search pipelines and their signal-to-noise ratio (SNR) is determined. Sensitive volume is estimated, by using Monte-Carlo (MC) integration, from the total number of injections added to the data, the number of injections that cross a chosen threshold on SNR and the astrophysical volume in which the injections are placed. So far, only fixed population models have been used in the estimation of binary black holes (BBH) merger rates. However, as the scope of population analysis broaden in terms of the methodologies and source properties considered, due to an increase in the number of observed gravitational wave (GW) signals, the procedure will need to be repeated multiple times at a large computational cost. In this letter we address the problem by performing a weighted MC integration. We show how a single set of generic injections can be weighted to estimate the sensitive volume for multiple population models; thereby greatly reducing the computational cost. The weights in this MC integral are the ratios of the output probabilities, determined by the population model and standard cosmology, and the injection probability, determined by the distribution function of the generic injections. Unlike analytical/semi-analytical methods, which usually estimate sensitive volume using single detector sensitivity, the method is accurate within statistical errors, comes at no added cost and requires minimal computational resources. [ABSTRACT FROM AUTHOR]

Generally, a magnetic target can be described with six parameters, three describing the position and three describing the magnetic moment. Due to a lack of sufficient components from one magnetometer, we need more than one magnetometer when locating the magnetic target. Thus, a magnetometer array should be designed. The baseline of the array is an important factor that affects the localization accuracy of the target. In this paper, we focus on the localization of a static target by using a scalar magnetometer array. We present the scalar magnetometer array with a cross-shaped structure. We propose a method of determining the optimal baseline according to the parameters of the magnetometer and detection requirements. In the method, we use the traditional signal-to-noise ratio (SNR) as a performance index, and obtain the optimal baseline of the array by using the Monte Carlo method. The proposed method of determining the optimal baseline is verified in simulation. The arrays with different baselines are used to locate a static magnetic target. The results show that the location performance is better when using the array with the optimal baseline determined by the proposed method. [ABSTRACT FROM AUTHOR]

Attenuation correction for PET-MR systems continues to be a challenging problem, particularly for body regions outside the head. The simultaneous acquisition of transmission scan based μ-maps and MR images on integrated PET-MR systems may significantly increase the performance of and offer validation for new MR-based μ-map algorithms. For the Biograph mMR (Siemens Healthcare), however, use of conventional transmission schemes is not practical as the patient table and relatively small diameter scanner bore significantly restrict radioactive source motion and limit source placement. We propose a method for emission-free coincidence transmission imaging on the Biograph mMR. The intended application is not for routine subject imaging, but rather to improve and validate MR-based μ-map algorithms; particularly for patient implant and scanner hardware attenuation correction. In this study we optimized source geometry and assessed the method’s performance with Monte Carlo simulations and phantom scans. We utilized a Bayesian reconstruction algorithm, which directly generates μ-map estimates from multiple bed positions, combined with a robust scatter correction method. For simulations with a pelvis phantom a single torus produced peak noise equivalent count rates (34.8 kcps) dramatically larger than a full axial length ring (11.32 kcps) and conventional rotating source configurations. Bias in reconstructed μ-maps for head and pelvis simulations was  ⩽4% for soft tissue and  ⩽11% for bone ROIs. An implementation of the single torus source was filled with 18F-fluorodeoxyglucose and the proposed method quantified for several test cases alone or in comparison with CT-derived μ-maps. A volume average of 0.095 cm−1 was recorded for an experimental uniform cylinder phantom scan, while a bias of  <2% was measured for the cortical bone equivalent insert of the multi-compartment phantom. Single torus μ-maps of a hip implant phantom showed significantly less artifacts and improved dynamic range, and differed greatly for highly attenuating materials in the case of the patient table, compared to CT results. Use of a fixed torus geometry, in combination with translation of the patient table to perform complete tomographic sampling, generated highly quantitative measured μ-maps and is expected to produce images with significantly higher SNR than competing fixed geometries at matched total acquisition time. [ABSTRACT FROM AUTHOR]

Based on weak lensing data from the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS), in this paper we study the mass–concentration (M–c) relation for ∼200 redMaPPer clusters in the fields. We extract the M–c relation by measuring the density profiles of individual clusters instead of using stacked weak lensing signals. By performing Monte Carlo simulations, we demonstrate that although the signal-to-noise ratio for each individual cluster is low, the unbiased M–c relation can still be reliably derived from a large sample of clusters by carefully taking into account the impacts of shape noise, cluster center offset, dilution effect from member or foreground galaxies, and the projection effect. Our results show that within error bars the derived M–c relation for redMaPPer clusters is in agreement with simulation predictions. There is a weak deviation in that the halo concentrations calibrated by Monte Carlo simulations are somewhat higher than that predicted from Planck cosmology. [ABSTRACT FROM AUTHOR]

A detailed 3D Monte Carlo simulation of the grid geometrical parameters in screen-film mammography (SFM) and digital mammography (DM) systems has been performed. A combination of IEC 60627:2013 international standard conditions and other more clinically relevant parameters were used for this simulation. Accuracy of our results has been benchmarked with previously published data and good agreement has been obtained. Calculations in a wide range of linear anti-scatter grid geometries have been carried out. The evaluated parameters for the SFM system were the Bucky factor (BF) and contrast improvement factor (CIF) and for the DM system it was signal difference-to-noise ratio improvement factor (SIF). The CIF parameter was chosen to be nearly the same as the commercial grade, the BF and SIF were significantly improved compared to commercial grids in use today. Our optimized grid parameters for the SFM system were lead strip thickness  µm, grid ratio and strip density lines/cm. And for the DM system these parameters were  µm, r = 3 and lines/cm. Both optimized grid sets have thinner d and higher N compared to the commercial grids. [ABSTRACT FROM AUTHOR]

We present paper six of the NIRSPEC Brown Dwarf Spectroscopic Survey, an analysis of multi-epoch, high-resolution (R ∼ 20,000) spectra of 25 field dwarf systems (3 late-type M dwarfs, 16 L dwarfs, and 6 T dwarfs) taken with the NIRSPEC infrared spectrograph at the W. M. Keck Observatory. With a radial velocity (RV) precision of ∼2 km s−1, we are sensitive to brown dwarf companions in orbits with periods of a few years or less given a mass ratio of 0.5 or greater. We do not detect any spectroscopic binary brown dwarfs in the sample. Given our target properties, and the frequency and cadence of observations, we use a Monte Carlo simulation to determine the detection probability of our sample. Even with a null detection result, our 1σ upper limit for very low mass binary frequency is 18%. Our targets included seven known, wide brown dwarf binary systems. No significant RV variability was measured in our multi-epoch observations of these systems, even for those pairs for which our data spanned a significant fraction of the orbital period. Specialized techniques are required to reach the high precisions sensitive to motion in orbits of very low-mass systems. For eight objects, including six T dwarfs, we present the first published high-resolution spectra, many with high signal to noise, that will provide valuable comparison data for models of brown dwarf atmospheres. [ABSTRACT FROM AUTHOR]

Excellent timing resolution is required to enhance the signal-to-noise ratio (SNR) gain available from the incorporation of time-of-flight (ToF) information in image reconstruction for positron emission tomography (PET). As the detector’s timing resolution improves, so does SNR, reconstructed image quality, and accuracy. This directly impacts the challenging detection and quantification tasks in the clinic. The recognition of these benefits has spurred efforts within the molecular imaging community to determine to what extent the timing resolution of scintillation detectors can be improved and develop near-term solutions for advancing ToF-PET. Presented in this work, is a method for calculating the Cramér–Rao lower bound (CRLB) on timing resolution for scintillation detectors with long crystal elements, where the influence of the variation in optical path length of scintillation light on achievable timing resolution is non-negligible. The presented formalism incorporates an accurate, analytical probability density function (PDF) of optical transit time within the crystal to obtain a purely mathematical expression of the CRLB with high-aspect-ratio (HAR) scintillation detectors. This approach enables the statistical limit on timing resolution performance to be analytically expressed for clinically-relevant PET scintillation detectors without requiring Monte Carlo simulation-generated photon transport time distributions. The analytically calculated optical transport PDF was compared with detailed light transport simulations, and excellent agreement was found between the two. The coincidence timing resolution (CTR) between two mm LYSO:Ce crystals coupled to analogue SiPMs was experimentally measured to be ps FWHM, approaching the analytically calculated lower bound within 6.5%. [ABSTRACT FROM AUTHOR]