Estimation Of Attenuation Coefficient Research Articles

A Neural Network Model for K(λ) Retrieval and Application to Global Kpar Monitoring.

Accurate estimation of diffuse attenuation coefficients in the visible wavelengths K d(λ) from remotely sensed data is particularly challenging in global oceanic and coastal waters. The objectives of the present study are to evaluate the applicability of a semi-analytical K d(λ) retrieval model (SAKM) and Jamet’s neural network model (JNNM), and then develop a new neural network K d(λ) retrieval model (NNKM). Based on the comparison of K d(λ) predicted by these models with in situ measurements taken from the global oceanic and coastal waters, all of the NNKM, SAKM, and JNNM models work well in K d(λ) retrievals, but the NNKM model works more stable and accurate than both SAKM and JNNM models. The near-infrared band-based and shortwave infrared band-based combined model is used to remove the atmospheric effects on MODIS data. The K d(λ) data was determined from the atmospheric corrected MODIS data using the NNKM, JNNM, and SAKM models. The results show that the NNKM model produces <30% uncertainty in deriving K d(λ) from global oceanic and coastal waters, which is 4.88-17.18% more accurate than SAKM and JNNM models. Furthermore, we employ an empirical approach to calculate K par from the NNKM model-derived diffuse attenuation coefficient at visible bands (443, 488, 555, and 667 nm). The results show that our model presents a satisfactory performance in deriving K par from the global oceanic and coastal waters with 20.2% uncertainty. The K par are quantified from MODIS data atmospheric correction using our model. Comparing with field measurements, our model produces ~31.0% uncertainty in deriving K par from Bohai Sea. Finally, the applicability of our model for general oceanographic studies is briefly illuminated by applying it to climatological monthly mean remote sensing reflectance for time ranging from July, 2002- July 2014 at the global scale. The results indicate that the high K d(λ) and K par values are usually found around the coastal zones in the high latitude regions, while low K d(λ) and K par values are usually found in the open oceans around the low-latitude regions. These results could improve our knowledge about the light field under waters at either the global or basin scales, and be potentially used into general circulation models to estimate the heat flux between atmosphere and ocean.

Emission-based estimation of lung attenuation coefficients for attenuation correction in time-of-flight PET/MR

In standard segmentation-based MRI-guided attenuation correction (MRAC) of PET data on hybrid PET/MRI systems, the inter/intra-patient variability of linear attenuation coefficients (LACs) is ignored owing to the assignment of a constant LAC to each tissue class. This can lead to PET quantification errors, especially in the lung regions. In this work, we aim to derive continuous and patient-specific lung LACs from time-of-flight (TOF) PET emission data using the maximum likelihood reconstruction of activity and attenuation (MLAA) algorithm. The MLAA algorithm was constrained for estimation of lung LACs only in the standard 4-class MR attenuation map using Gaussian lung tissue preference and Markov random field smoothness priors. MRAC maps were derived from segmentation of CT images of 19 TOF-PET/CT clinical studies into background air, lung, soft tissue and fat tissue classes, followed by assignment of predefined LACs of 0, 0.0224, 0.0864 and 0.0975 cm−1, respectively. The lung LACs of the resulting attenuation maps were then estimated from emission data using the proposed MLAA algorithm. PET quantification accuracy of MRAC and MLAA methods was evaluated against the reference CT-based AC method in the lungs, lesions located in/near the lungs and neighbouring tissues. The results show that the proposed MLAA algorithm is capable of retrieving lung density gradients and compensate fairly for respiratory-phase mismatch between PET and corresponding attenuation maps. It was found that the mean of the estimated lung LACs generally follow the trend of the reference CT-based attenuation correction (CTAC) method. Quantitative analysis revealed that the MRAC method resulted in average relative errors of −5.2 ± 7.1% and −6.1 ± 6.7% in the lungs and lesions, respectively. These were reduced by the MLAA algorithm to −0.8 ± 6.3% and −3.3 ± 4.7%, respectively. In conclusion, we demonstrated the potential and capability of emission-based methods in deriving patient-specific lung LACs to improve the accuracy of attenuation correction in TOF PET/MR imaging, thus paving the way for their adaptation in the clinic.

A New Statistical WRELAX Algorithm Under Nakagami Multipath Channel Based on Delay Power Spectrum Characteristic

Multipath delay estimation plays an important role in wireless channel estimation, equalization, and synchronization. Weighted Fourier transform and relaxation (WRELAX) algorithm is frequently used for its high resolution and good convergence property. However, the WRELAX algorithm is prone to false estimated delays and irregular multipath sorting under Nakagami-based multipath channel, which is a more practical model than the traditional Rice or Rayleigh-based multipath model, because of the oscillatory cost function property between the received and the known transmitted signals. Given relatively stable characteristics and delay power spectrum distribution characteristics of the wireless channel, together with the principle that the statistical probability of the true estimated delays is larger than that of the false ones through statistical detection, this study proposes a delay power spectrum characteristic-based statistical WRELAX time delay estimation algorithm. The improved algorithm excludes false estimated paths and sorts the delays in size order simultaneously by establishing a two-dimensional relation graph composed of the superposition value of estimated attenuation coefficient and their response-estimated delays. Simulation under three typical Nakagami-based slow fading multipath channels shows that the proposed algorithm has good accuracy and robustness, and the cost of complexity increased by only a few times.

A functional regression model for predicting optical depth and estimating attenuation coefficients in sea-ice covers near Resolute Passage, Canada

AbstractThe spectral dependence of natural light transmittance on ice algae concentration and snow depth in Arctic sea ice provides the potential to study the changing bottom-ice ecosystem using optical relationships. In this paper, we consider the use of functional data analysis techniques to describe such relationships. Specifically, we created a functional regression model describing spectral optical depth as a function of chlorophyll a concentration, snow depth and ice thickness. Measurements of the aforementioned covariates and surface and transmitted spectral irradiance were collected on landfast first-year sea ice in the High Arctic near Resolute Passage, Canada, during the spring of 2011 and used as model input. The derived model explains 75–84.5% of the variation in the observed spectral optical depth curves. No prior assumptions of snow/sea-ice optical properties are required in the application of this technique, as the model estimates the attenuation coefficients of each covariate using only the measurements mentioned above. The quality and simplicity of the model highlight the potential of functional data analysis to study the Arctic marine ecosystem.

Attenuation Coefficient Estimation of the Healthy Human Thyroid In Vivo

Previous studies have demonstrated that attenuation coefficients can be useful towards characterizing thyroid tissues. In this work, ultrasonic attenuation coefficients were estimated from healthy human thyroids in vivo using a clinical scanner. The selected subjects were five young, healthy volunteers (age: 26 ± 6 years old, gender: three females, two males) with no reported history of thyroid diseases, no palpable thyroid nodules, no smoking habits, and body mass index less than 30kg/m2. Echographic examinations were conducted by a trained sonographer using a SonixTouch system (Ultrasonix Medical Corporation, Richmond, BC) equipped with an L14-5 linear transducer array (nominal center frequency of 10MHz, transducer footprint of 3.8cm). Radiofrequency data corresponding to the collected echographic images in both transverse and longitudinal views were digitized at a sampling rate of 40MHz and processed with Matlab codes (MathWorks, Natick, MA) to estimate attenuation coefficients using the spectral log difference method. The estimation was performed using an analysis bandwidth spanning from 4.0 to 9.0MHz. The average value of the estimated ultrasonic attenuation coefficients was equal to 1.34 ± 0.15dB/(cm.MHz). The standard deviation of the estimated average attenuation coefficient across different volunteers suggests a non-negligible inter-subject variability in the ultrasonic attenuation coefficient of the human thyroid.

Noninvasive Characterization of Locally Advanced Breast Cancer Using Textural Analysis of Quantitative Ultrasound Parametric Images

PURPOSE: The identification of tumor pathologic characteristics is an important part of breast cancer diagnosis, prognosis, and treatment planning but currently requires biopsy as its standard. Here, we investigated a noninvasive quantitative ultrasound method for the characterization of breast tumors in terms of their histologic grade, which can be used with clinical diagnostic ultrasound data. METHODS: Tumors of 57 locally advanced breast cancer patients were analyzed as part of this study. Seven quantitative ultrasound parameters were determined from each tumor region from the radiofrequency data, including mid-band fit, spectral slope, 0-MHz intercept, scatterer spacing, attenuation coefficient estimate, average scatterer diameter, and average acoustic concentration. Parametric maps were generated corresponding to the region of interest, from which four textural features, including contrast, energy, homogeneity, and correlation, were determined as further tumor characterization parameters. Data were examined on the basis of tumor subtypes based on histologic grade (grade I versus grade II to III). RESULTS: Linear discriminant analysis of the means of the parametric maps resulted in classification accuracy of 79%. On the other hand, the linear combination of the texture features of the parametric maps resulted in classification accuracy of 82%. Finally, when both the means and textures of the parametric maps were combined, the best classification accuracy was obtained (86%). CONCLUSIONS: Textural characteristics of quantitative ultrasound spectral parametric maps provided discriminant information about different types of breast tumors. The use of texture features significantly improved the results of ultrasonic tumor characterization compared to conventional mean values. Thus, this study suggests that texture-based quantitative ultrasound analysis of in vivo breast tumors can provide complementary diagnostic information about tumor histologic characteristics.

MRI compatible head phantom for ultrasound surgery

ObjectiveDevelop a magnetic resonance imaging (MRI) compatible head phantom with acoustic attenuation closely matched to the human attenuation, and suitable for testing focused ultrasound surgery protocols. Materials and methodsImages from an adult brain CT scan were used to segment the skull bone from adjacent cerebral tissue. The segmented model was manufactured in a 3-D printer using (Acrylonitrile Butadiene Styrene) ABS plastic. The cerebral tissue was mimicked by an agar–evaporated milk–silica gel (2% w/v–25% v/v–1.2% w/v) which was molded inside a skull model. ResultsThe measured attenuation of the ABS skull was 16dB/cmMHz. The estimated attenuation coefficient of the gel replicating brain tissue was 0.6dB/cmMHz. The estimated agar–silica gel’s T1 and T2 relaxation times in a 1.5Tesla magnetic field were 852ms and 66ms respectively. The effectiveness of the skull to reduce ultrasonic heating was demonstrated using MRI thermometry. ConclusionDue to growing interest in using MRI guided focused ultrasound (MRgFUS) for treating brain cancer and its application in sonothrombolysis, the proposed head phantom can be utilized as a very useful tool for evaluating ultrasonic protocols, thus minimizing the need for animal models and cadavers.

Preliminary evaluation of the MLAA algorithm with the Philips Ingenuity PET/MR.

Combined PET/MR is a promising tool for simultaneous investigation of soft tissue morphology and function. However, contrary to CT, MR images do not provide information on photon attenuation in tissue. In the currently available systems issue is solved by synthesizing attenuation maps from MR images using segmentation algorithms. This approach has been shown to provide reason-able results in most cases. However, sporadically occurring segmentation errors can cause serious problems. Recently, algorithms for simultaneous estimation of attenuation and tracer distribution (MLAA) have been introduced. So far, validity of MLAA has mainly been demonstrated in simulated data. We have integrated the MLAA algorithm [2] into the THOR reconstruction [1]. An evaluation of MLAA was performed using both phantom and patient data acquired with the Ingenuity PET/MR. Phantom data were acquired using a whole body phantom with three cylindrical inserts filled with different substances (plastic, air, glycerol). MLAA-estimated mu-maps of the phantom were compared to the mu-maps resulting from transmission measurements with an ECAT HR+ scanner. We also performed a first qualitative evaluation of the attenuation maps obtained in patient studies. Evaluation of the phantom study showed good concordance between measured and estimated attenuation coefficients for all types of substances used in the phantom. Evaluation of patient data showed some substantial improvements of the MLAA attenuation maps compared to the segmented MR-based attenuation maps. Preliminary results show that for the Philips Ingenuity PET/MR scanner the MLAA algorithm allows to obtain attenuation maps which outperform the MR based maps in several aspects. However, a more detailed analysis is still required to address the question of possible cross-talks in regions with high activity. Additionally, MLAA algorithm substantially increases computational burden leading to long processing times, which makes it currently impractical for clinical application.

Diffuse Attenuation Coefficients for East Antarctic Pack Ice and Snow at Ultraviolet and Visible Wavelengths

Declining stratospheric ozone concentrations have led to higher levels of ultraviolet (UV) B (UVB) radiation at the Earth's surface, particularly in Antarctic spring time. Increased exposure to UVB radiation can decrease the productivity of sea-ice algae, as well as cause damage to organisms living in the clear water beneath the Antarctic pack ice. Conversely, sea-ice algae and other photosynthetic organisms rely on photosynthetically active radiation (PAR) to drive and sustain growth. Field work performed during the 2007 Australian Antarctic Program Sea Ice Physics and Ecosystem eXperiment voyage to the East Antarctic sea-ice zone allowed the estimation of diffuse attenuation coefficients for pack ice and the overlying snow at UV wavelengths (305, 313, 320, 340, 380, and 395 nm) and for PAR. The UV attenuation coefficients were 9.6-12.7 m-1 for snow and 1.57-2.05 m-1 for pack ice. The PAR attenuation coefficients were 10.5 m-1 (snow) and 1.52 m-1 (pack ice). The attenuation coefficients for erythemally weighted UVB radiation were 11.3 m-1 (snow) and 1.82 m-1 (pack ice). The analysis also estimated the reflection coefficient (albedo) of snow as 0.67 for UV wavelengths and 0.68 for PAR, but the snow cover was not always optically thick.

Joint estimation of modal attenuation and velocity from multichannel surface wave data

We evaluated a method for the simultaneous analysis of velocity and attenuation of multichannel surface wave data. It allowed us to estimate the phase velocity and attenuation curves using an array of receivers, possibly unevenly spaced, and a set of multiple shots at different locations. After reviewing the properties of surface waves in dissipative media, the estimation algorithm was evaluated. It was based on the estimation of the complex wavenumber of multiple normal modes. It can be considered as a high-resolution subspace-based method able to deal with irregularly sampled multichannel-multishot data. The interference between multiple modes was considered without the need of a prior specific multimode Rayleigh spreading function, so that multiple modal attenuation curves can be extracted. The validity of the approach was tested using synthetic data, with small and large mode interference, as well as with multimode real data. The benefits and the robustness of the proposed method were particularly relevant with data with multiple modes. The possibility of considering multiple shot points into a receiver array allowed the increase of the modal resolution without increasing the receiver aperture, thus without compromising the lateral resolution. The estimation of the modal attenuation coefficient enabled the estimation of the subsurface material damping ratio, and the definition of a dissipative propagation model.

New strategy to improve estimation of diffuse attenuation coefficient for highly turbid inland waters

The diffuse attenuation coefficient, Kd(λ), is an important water optical property. Detection of Kd(λ) by means of remote sensing can provide significant assistance in understanding water environment conditions and many biogeochemical processes. Even when existing algorithms exhibit good performance in clear open ocean and turbid coastal waters, accurate quantification of highly turbid inland water bodies can still be a challenge due to their bio-optical complexity. In this study, we examined the performance of two typical pre-existing Kd(490) models in inland water bodies from Lake Taihu, Lake Chaohu, and the Three Gorges Reservoir in China. On the basis of water optical classification, new Kd(490) models were developed for these waters by means of the support vector machine approach. The obtained results showed that the two pre-existing Kd(490) models presented relatively large errors by comparison with the new models, with mean absolute percentage error (MAPE) values above ~30%. More importantly, among the new models, type-specific models generally outperformed the aggregated model. For water classified as Type 1 + Type 2, the type-specific model produced validation errors with MAPE = 16.8% and RMSE = 0.98 m−1. For water classified as Type 3, the MAPE and RMSE of the type-specific model were found to be 18.8% and 1.85 m−1, respectively. The findings in this study demonstrate that water classification (prior to algorithm development) is needed for the development of excellent Kd(490) retrieval algorithms, and the type-specific models thus developed are an important supplement to existing Kd(490) retrieval models for highly turbid inland waters.

Signal to noise ratio comparisons for ultrasound attenuation slope estimation algorithms

Attenuation imaging has a promising role in the detection of tissue abnormalities. The authors have previously compared three different frequency domain ultrasound attenuation estimation methods, for accuracy and bias. The mean estimated attenuation value in a region of interest has been the determining factor of how well a method performs; however, the noise level has not been quantified for attenuation estimated using different methods. The authors compare three different frequency domain ultrasound attenuation estimation methods [the reference phantom method (RPM), the centroid downshift method (CEN), and the hybrid method (HYB)] using the signal to noise ratio (SNR) metric. Both simulated and experimental tissue-mimicking phantoms are used in the performance comparison study, evaluating the impact of the variation in acoustical properties. For attenuation estimation in a tissue-mimicking phantom with a known attenuation coefficient of 0.5 dB/cm/MHz, all the three methods estimated the attenuation coefficient to be ≈ 0.49 dB/cm/MHz for a transmit center frequency of 6 MHz, however, the signal to noise ratio obtained was found to be 8.5, 5.7, and 2.2 for the HYB, RPM, and CEN methods, respectively. These results demonstrate the need for the SNR metric in the comparison of different algorithms and to evaluate the impact of varying different ultrasound system and tissue parameters. In this paper, the authors demonstrate that although the estimated mean attenuation value with a region of interest may be closely estimated using different methods, the signal to noise ratio obtained of the estimates can vary significantly. The centroid downshift method presented with the lowest signal-to-noise ratio of the methods compared. The hybrid method was the least susceptible to changes in the acoustical properties and provided unbiased attenuation coefficient estimates with the highest signal-to-noise ratios.

Object Detection by Estimation of the Spectral Attenuation Coefficient in the Submerged Medium

Underwater object detection has a considerable impact in the field of ocean technology. This paper presents a techniqueto detect a submerged object based on the medium's spectral attenuation coefficient by applying Beer-Lambert Law. The value of this coefficient is a function of the medium's composition, depth of the object,and wavelength of incident light. Experiments were performed in a swimming pool using objects of different colors at different depths to validate the mathematical model for object detection.

Depth-resolved model-based reconstruction of attenuation coefficients in optical coherence tomography

We present a method, based on a single scattering model, to calculate the attenuation coefficient of each pixel in optical coherence tomography (OCT) depth profiles. Numerical simulations were used to determine the model's response to different depths and attenuation coefficients. Experiments were performed on uniform and layered phantoms with varying attenuation coefficients. They were measured by a 1300 nm OCT system and their attenuation coefficients were evaluated by our proposed method and by fitting the OCT slope as the gold standard. Both methods showed largely consistent results for the uniform phantoms. On the layered phantom, only our proposed method accurately estimated the attenuation coefficients. For all phantoms, the proposed method largely reduced the variability of the estimated attenuation coefficients. The method was illustrated on an in-vivo retinal OCT scan, effectively removing common imaging artifacts such as shadowing. By providing localized, per-pixel attenuation coefficients, this method enables tissue characterization based on attenuation coefficient estimates from OCT data.

Dual energy CT for attenuation correction with PET/CT

The authors evaluate the energy dependent noise and bias properties of monoenergetic images synthesized from dual-energy CT (DECT) acquisitions. These monoenergetic images can be used to estimate attenuation coefficients at energies suitable for positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging. This is becoming more relevant with the increased use of quantitative imaging by PET/CT and SPECT/CT scanners. There are, however, potential variations in the noise and bias of synthesized monoenergetic images as a function of energy. The authors used analytic approximations and simulations to estimate the noise and bias of synthesized monoenergetic images of water-filled cylinders with different shapes and the NURBS-based cardiac-torso (NCAT) phantom from 40 to 520 keV, the range of SPECT and PET energies. The dual-kVp spectra were based on the GE Lightspeed VCT scanner at 80 and 140 kVp with added filtration of 0.5 mm Cu. The authors evaluated strategies of noise suppression with sinogram smoothing and dose minimization with reduction of tube currents at the two kVp settings. The authors compared the impact of DECT-based attenuation correction with single-kVp CT-based attenuation correction on PET quantitation for the NCAT phantom for soft tissue and high-Z materials of bone and iodine contrast enhancement. Both analytic calculations and simulations displayed the expected minimum noise value for a synthesized monoenergetic image at an energy between the mean energies of the two spectra. In addition the authors found that the normalized coefficient of variation in the synthesized attenuation map increased with energy but reached a plateau near 160 keV, and then remained constant with increasing energy up to 511 keV and beyond. The bias was minimal, as the linear attenuation coefficients of the synthesized monoenergetic images were within 2.4% of the known true values across the entire energy range. Compared with no sinogram smoothing, sinogram smoothing can dramatically reduce noise in the DECT-derived attenuation map. Through appropriate selection of tube currents for high and low kVp scans, DECT can deliver roughly the same amount of radiation dose as that of a single kVp CT scan, but could be used for PET attenuation correction with reduced bias in contrast agent regions by a factor of ≈ 2.6 and slightly reduced RMSE for the total image. When DECT is used for attenuation correction at higher energies, there is a noise amplification that is dependent on the energy of the synthesized monoenergetic image of linear attenuation coefficients. Sinogram smoothing reduces the noise amplification in DECT-derived attenuation maps without increasing bias. With an appropriate selection of CT techniques, a DECT scan with the same radiation dose as a single CT scan can result in a PET image with improved quantitative accuracy.

A numeric evaluation of attenuation from ambient noise correlation functions

The ambient noise correlation function (NCF) calculated between seismic stations contains, under appropriate conditions, accurate travel time information. However, NCF amplitudes are highly debated due to noise source intensity and distribution, seismic intrinsic attenuation, scattering, and elastic path effects such as focusing and defocusing. We prove with various numerical simulations that the NCFs calculated for a uniformly dispersive medium using the coherency method preserve accurate geometrical spreading and attenuation decay. We show that for a wide range of noise source distributions, the coherency of the noise correlation functions matches a Bessel function decaying exponentially with a specific attenuation coefficient. Conditions needed to obtain these results include averaging over long enough time intervals, a uniformly distributed seismic network, and a good distribution of far‐field noise sources. We also show that the estimated attenuation coefficient corresponds to the interstation and not the noise‐source‐to‐receiver structure.

Prospects for in vivo estimation of photon linear attenuation coefficients using postprocessing dual‐energy CT imaging on a commercial scanner: Comparison of analytic and polyenergetic statistical reconstruction algorithms

Accurate patient-specific photon cross-section information is needed to support more accurate model-based dose calculation for low energy photon-emitting modalities in medicine such as brachytherapy and kilovoltage x-ray imaging procedures. A postprocessing dual-energy CT (pDECT) technique for noninvasive in vivo estimation of photon linear attenuation coefficients has been experimentally implemented on a commercial CT scanner and its accuracy assessed in idealized phantom geometries. Eight test materials of known composition and density were used to compare pDECT-estimated linear attenuation coefficients to NIST reference values over an energy range from 10 keV to 1 MeV. As statistical image reconstruction (SIR) has been shown to reconstruct images with less random and systematic error than conventional filtered backprojection (FBP), the pDECT technique was implemented with both an in-house polyenergetic SIR algorithm, alternating minimization (AM), as well as a conventional FBP reconstruction algorithm. Improvement from increased spectral separation was also investigated by filtering the high-energy beam with an additional 0.5 mm of tin. The law of propagated uncertainty was employed to assess the sensitivity of the pDECT process to errors in reconstructed images. Mean pDECT-estimated linear attenuation coefficients for the eight test materials agreed within 1% of NIST reference values for energies from 1 MeV down to 30 keV, with mean errors rising to between 3% and 6% at 10 keV, indicating that the method is unbiased when measurement and calibration phantom geometries are matched. Reconstruction with FBP and AM algorithms conferred similar mean pDECT accuracy. However, single-voxel pDECT estimates reconstructed on a 1 × 1 × 3 mm(3) grid are shown to be highly sensitive to reconstructed image uncertainty; in some cases pDECT attenuation coefficient estimates exhibited standard deviations on the order of 20% around the mean. Reconstruction with the statistical AM algorithm led to standard deviations roughly 40% to 60% less than FBP reconstruction. Additional tin filtration of the high energy beam exhibits similar pDECT estimation accuracy as the unfiltered beam, even when scanning with only 25% of the dose. Using the law of propagated uncertainty, low Z materials are found to be more sensitive to image reconstruction errors than high Z materials. Furthermore, it is estimated that reconstructed CT image uncertainty must be limited to less than 0.25% to achieve a target linear-attenuation coefficient estimation uncertainty of 3% at 28 keV. That pDECT supports mean linear attenuation coefficient measurement accuracies of 1% of reference values for energies greater than 30 keV is encouraging. However, the sensitivity of the pDECT measurements to noise and systematic errors in reconstructed CT images warrants further investigation in more complex phantom geometries. The investigated statistical reconstruction algorithm, AM, reduced random measurement uncertainty relative to FBP owing to improved noise performance. These early results also support efforts to increase DE spectral separation, which can further reduce the pDECT sensitivity to measurement uncertainty.

Out-of-field activity in the estimation of mean lung attenuation coefficient in PET/MR

In clinical PET/MR, photon attenuation is a source of potentially severe image artifacts. Correction approaches include those based on MR image segmentation, in which image voxels are classified and assigned predefined attenuation coefficients to obtain an attenuation map. In whole-body imaging, however, mean lung attenuation coefficients (LAC) can vary by a factor of 2, and the choice of inappropriate mean LAC can have significant impact on PET quantification. Previously, we proposed a method combining MR image segmentation, tissue classification and Maximum Likelihood reconstruction of Attenuation and Activity (MLAA) to estimate mean LAC values. In this work, we quantify the influence of out-of-field (OOF) accidental coincidences when acquiring data in a single bed position. We therefore carried out GATE simulations of realistic, whole-body activity and attenuation distributions derived from data of three patients. A bias of 15% was found and significantly reduced by removing OOF accidentals from our data, suggesting that OOF accidentals are the major contributor to the bias. We found approximately equal contributions from OOF scatter and OOF randoms, and present results after correction of the bias by rescaling of results. Results using temporal subsets suggest that 30-second acquisitions may be sufficient for estimation mean LAC with less than 5% uncertainty if mean bias can be corrected for.

On the response of GdAlO3:Ce powder scintillators

The aim of the present study was to investigate the luminescence efficiency (XLE) of gadolinium aluminum perovskite (GdAlO3:Ce) powder scintillator. This powder phosphor, also known as GAP:Ce scintillator, is a non-hygroscopic material, emitting blue light with short decay time. For the purposes of this study, five scintillating screens with coating thicknesses, 14.7, 31.0, 53.7, 67.2 and 121.1mg/cm2, were prepared in our laboratory from GdAlO3:Ce powder (Phosphor Technology, Ltd) by sedimentation on silica substrates. The light emitted by the phosphors under investigation was evaluated by performing measurements of the absolute luminescence efficiency (AE), X-ray luminescence efficiency and detector quantum gain (DQG) under X-ray exposure conditions with tube voltages ranging from 50 to 140kV. The quantum detection efficiency (QDE) and energy absorption efficiency (EAE) were also evaluated. The spectral compatibility of GdAlO3:Ce, with various existing optical detectors, was investigated after emission spectra measurements. A theoretical model, describing radiation and light transfer, was used to fit experimental AE data. This has allowed the estimation of optical attenuation coefficients of the scintillator. GdAlO3:Ce exhibited higher QDE and EAE values, compared to aluminium perovskite (YAlO3:Ce) but lower absolute efficiency values. Absolute efficiency was found to increase with increasing X-ray tube voltage, although for values higher than 120kVp a decrease was observed.

Retrieval of diffuse attenuation coefficient in the China seas from surface reflectance

Accurate estimation of the diffuse attenuation coefficient is important for our understanding the availability of light to underwater communities, which provide critical information for the China seas ecosystem. However, algorithm developments and validations of the diffuse attenuation coefficient in the China seas have been seldom performed before and therefore our knowledge on the quality of retrieval of the diffuse attenuate coefficient is poor. In this paper optical data at 306 sites collected in coastal waters of the China seas between July 2000 and February 2004 are used to evaluate three typical existing Kd(490) models. The in situ Kd(490) varied greatly among different sites from 0.029 m(-1) to 10.3 m(-1), with a mean of 0.92 ± 1.59 m(-1). Results show that the empirical model and the semi-analytical model significantly underestimate the Kd(490) value, with estimated mean values of 0.24 m(-1) and 0.5 m(-1), respectively. The combined model also shows significant differences when the in situ Kd(490) range from 0.2 m(-1) to 1 m(-1). Thus, the present study proposes that the three algorithms cannot be directly used to appropriately estimate Kd(490) in the turbid coastal waters of the China seas without a fine tuning for regional applications. In this paper, new Kd(490) algorithms are developed based on the semi-analytical retrieval of the absorption coefficient a(m(-1)) and the backscattering coefficient bb(m(-1)) from the reflectance at two wavelengths, 488 and 667 nm for the Moderate Resolution Imaging Spectroradiometer (MODIS) and 490 and 705 nm for the Medium Resolution Imaging Spectrometer (MERIS) applications, respectively. With the new approaches, the mean ratio and the relative percentage difference are 1.05 and 4.6%, respectively, based on an independent in situ data set. Furthermore, the estimates are reliable within a factor of 1.9 (95% confidence interval). Comparisons also show that the Kd(490) derived with the new algorithms are well correlated with the in situ measurements. Our results showed a good improvement in the estimation for Kd(490) using the new approaches, contrasting with existing empirical, semi-analytical and combined models. Therefore, we propose the new approaches for accurate retrieval of Kd(490) in the China seas.