Scatter correction

Quantitative tissue classification using dual-energy CT has the potential to improve accuracy in radiation therapy dose planning as it provides more information about material composition of scanned objects than the currently used methods based on single-energy CT. One problem that hinders successful application of both single-and dualenergy CT is the presence of beam hardening and scatter artifacts in reconstructed data. Current pre-and post-correction methods used for image reconstruction often bias CT numbers and thus limit their applicability for quantitative tissue classification. Here we demonstrate simulation studies with a novel iterative algorithm that decomposes every soft tissue voxel into three base materials: water, protein and adipose. The results demonstrate that beam hardening artifacts can effectively be removed and accurate estimation of mass fractions of all base materials can be achieved. In the future, the algorithm may be developed further to include segmentation of soft and bone tissue and subsequent bone decomposition, extension from 2-D to 3-D and scatter correction.

Accurate absorbed dose calculations are important for a proper dose planning in internal radionuclide therapy. The activity distribution must be measured and the target volume defined. This can be done with single photon emission tomography (SPET) if proper attenuation and scatter correction are employed. This study investigated the calculation of the activity and the volume of different spherical sources. These two parameters are essential for a proper dose calculation. The scatter and attenuation correction method is based on spatially variant scatter functions and density maps. The volume calculation method is based on obtaining a threshold from a grey-level histogram. Both point sources and spheres of different diameters containing technetium-99m were placed in different locations in an elliptical water phantom and imaged by SPET. The activity and the volume of the spheres were calculated from the SPET images and compared with known activities. Results show a quantification of activity within 10% for most of the sources. Important influences on the quantification are (a) the presence of artefacts due to improper reconstruction and (b) the finite spatial resolution which affects the total number of counts within the determined volume.

We compared simultaneous dual-radionuclide stress and rest myocardial perfusion imaging (MPI) with a novel solid-state cardiac camera and a conventional SPECT camera with separate stress and rest acquisitions. Methods-24 consecutive patients (64.5 ± 11.8 years, 16 men) were injected with 74 MBq of 201 Tl (rest) and 250 MBq 99m Tc-MIBI (stress). Conventional MPI acquisition times for stress and rest were 21 min and 16 min, respectively. A simultaneous dual-radionuclide (DR) 15 minute list mode gated acquisition was performed on D-SPECT (Spectrum-dynamics, Caesarea, Israel). The DR D-SPECT data were processed using a spillover and scatter correction method. We compared DR D-SPECT images with conventional SPECT images by visual analysis employing the 17-segment model and a 5-point scale (0=normal, 4=absent) to calculate the summed stress and rest scores (SSS and SRS, respectively) and the % visual perfusion defect (TPD) at stress and rest, by dividing the stress and rest scores, respectively, by 68 and multiplying by 100. TPD <5% was considered normal. Image quality was assessed on a 4-point scale (1=poor, 4=very good) and gut activity was assessed on a 4-point scale (0=none, 3=high). MPI was abnormal at stress in 17 patients and at rest in 9 patients. In the 17 abnormal stress studies DR D-SPECT MPI was abnormal in 113 vs. 93 abnormal segments by conventional MPI. In the nine abnormal rest studies DR D-SPECT was abnormal in 45 vs. 48 segments abnormal by conventional MPI. SSS, SRS, TPD stress and TPD rest on conventional SPECT and DR D-SPECT highly correlated (r=0.9790, 0.9694, 0.9784, 0.9710, respectively; p<0.0001 for all). In addition, 6 patients had significantly larger perfusion defects on DR D-SPECT stress images, including five of 11 patients who were imaged earlier on D-SPECT than conventional SPECT. Conclusion-D-SPECT enables fast and high quality simultaneous DR MPI in a single imaging session with comparable diagnostic performance and image quality to conventional SPECT. Modifications of the injected doses and of the imaging protocol with DR D-SPECT may enable

Titre Median solution and noise sorting, a reconstruction algorithm for emission tomography with large hole collimator Type de publication Article de revue Auteur Jeanguillaume, Christian [1], Ines, BOUALI [2], istvan, MAROS [3], faurie, Julia [4] Editeur IEEE Type Article scientifique dans une revue à comité de lecture Année

Introduction Quality control is an important phenomenon in nuclear medicine imaging. A Jaszczak SPECT Phantom provides consistent performance information for any SPECT or PET system. This article describes the simulation of a Jaszczak phantom and creating an executable phantom file for comparing assessment of SPECT cameras using SIMIND Monte Carlo simulation program which is well-established for SPECT. Materials and Methods The simulation was based on a Deluxe model of Jaszczak Phantom with defined geometry. Quality control tests were provided together with initial imaging example and suggested use for the assessment of parameters such as spatial resolution, limits of lesion detection, and contrast comparing with a Siemens E.Cam SPECT system. Results The phantom simulation was verified by matching tomographic spatial resolution, image contrast, and also uniformity compared with the experiment SPECT of the phantom from filtered backprojection reconstructed images of the spheres and r...

In preclinical Single Photon Emission Tomography (SPECT), absolute quantification is interesting, expressed in percentage of injected radioactive dose per gram of tissue. This allows for accurate evaluation of disease progression and precise follow-up studies without the need for sacrificing animals. Accurate modeling of image degrading effects is currently under development for isotopes different from 99m Tc. The aim of this work is to develop absolute micro-SPECT quantification for three different isotopes: 99m Tc, 111 In and 125 I. This selection of isotopes covers a wide range of energies, is pre-clinically relevant and allows us to optimally validate the algorithms used for image reconstruction. Furthermore, we will mix these isotopes with additional iodine-based CT contrast agent, to mimic contrast-enhanced SPECT/CT protocols. For each isotope, both a calibration phantom and three 1ml vials were scanned on the CZT-based FLEX Triumph-I scanner (GM-I). The calibration phantom allows the conversion of reconstructed voxel counts to MBq/ml. The 3-vial phantom consists of 3 different concentrations of radioactivity. Two vials contain iodine-based CT contrast agent to significantly increase the attenuation. All datasets were reconstructed using a GPUbased reconstruction algorithm, which includes resolution recovery, pinhole penetration, geometrical sensitivity correction, scatter correction and attenuation correction. We show good quantification for 99m Tc and 111 In. The absolute quantification of 125 I is suboptimal, due to insufficient scatter correction. No influence can be seen when iodine-based CT contrast agent is used together with 125 I.

In preclinical Single Photon Emission Tomography (SPECT), absolute quantification is interesting, expressed in percentage of injected radioactive dose per gram of tissue. This allows for accurate evaluation of disease progression and precise follow-up studies without the need for sacrificing animals. Accurate modeling of image degrading effects is currently under development for isotopes different from 99m Tc. The aim of this work is to develop absolute micro-SPECT quantification for three different isotopes: 99m Tc, 111 In and 125 I. This selection of isotopes covers a wide range of energies, is pre-clinically relevant and allows us to optimally validate the algorithms used for image reconstruction. Furthermore, we will mix these isotopes with additional iodine-based CT contrast agent, to mimic contrast-enhanced SPECT/CT protocols. For each isotope, both a calibration phantom and three 1ml vials were scanned on the CZT-based FLEX Triumph-I scanner (GM-I). The calibration phantom allows the conversion of reconstructed voxel counts to MBq/ml. The 3-vial phantom consists of 3 different concentrations of radioactivity. Two vials contain iodine-based CT contrast agent to significantly increase the attenuation. All datasets were reconstructed using a GPUbased reconstruction algorithm, which includes resolution recovery, pinhole penetration, geometrical sensitivity correction, scatter correction and attenuation correction. We show good quantification for 99m Tc and 111 In. The absolute quantification of 125 I is suboptimal, due to insufficient scatter correction. No influence can be seen when iodine-based CT contrast agent is used together with 125 I.

Diffuse near-infrared reflectance spectroscopy has traditionally been an analytical technique for determining chemical compositions in a sample. We will, in this paper, focus on light scattering effects and their ability to determine the mean particle sizes of powders. The reflectance data of NaCl, broken glass, and sorbitol powders are linearized and submitted to the Multiplicative Scatter Correction (MSC), and the ensuing parameters are used in subsequent multivariate calibrations. The results indicate that particle size can, to a large degree, be determined from NIR reflectance data for a given type of powder. Up to 99% of the partical size variance was explained by the regression.

The capability of near infrared reflectance spectroscopy (NIRS) was evaluated to predict the content of total ash (TA), crude protein (CP), crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF) and metabolizable energy (ME); as well as pH and ammonia nitrogen content (N-NH 3 ), in pasture silage, with and without additives. Nine hundred and twenty dried and ground samples of pasture silage, with known chemical composition, were scanned over the visible and NIR region (400 to 2500 nm) at 2 nm intervals. Calibration equations were developed by modified partial least square regression models (MPLS) with different mathematical treatments and light scatter correction as standard normal variation and Detrend (SNV & D) of the spectra. For each parameter, the optimum calibration was evaluated on the basis of the cross validation determination coefficient (1-VR) and standard error of cross validation (SECV). NIRS showed a high predictive ability, with 1-VR > 0.89 and SECV (%) of 5.14, 6.69, 9.96, 16.01 and 9.15 for A, CP, CF, NDF and ADF, respectively. NIRS showed moderate accuracy for ME, with 1-VR > 0.87, SECV: 0.07 Mcal kg -1 and low accuracy, although with feasibility as a ranking method, for pH and N-NH 3 , with 1-VR > 0.72 and SECV of 0.14 and 1.49, respectively. It was concluded that the equations obtained can be used to predict the nutritional composition of pasture silages.

A new generation of commercial animal PET cameras may accelerate drug development by streamlining preclinical testing in laboratory animals. However, little information on the feasibility of using these machines for quantitative PET in small animals is available. Here we investigate the reproducibility of microPET imaging of (11)C-raclopride in the rat brain and the effects of tracer-specific activity and photon scatter correction on measures of D2 receptor (D2R) availability. Sprague-Dawley rats (422 +/- 29 g; n = 7) were anesthetized with ketamine/xylazine and catheterized for tail vein injection of (11)C-raclopride. Each animal was positioned prone in the microPET, centering the head in the field of view. MicroPET data was collected for 60 min-starting at (11)C-raclopride injection-and binned into 24 time frames (6 x 10 s, 3 x 20 s, 8 x 60 s, 4 x 200 s, 3 x 600 s). In 3 studies, (11)C-raclopride was administered a second time in the same animal, with 2-4 h between injections. In ...

High resolution images in PET based on small individual detectors are obtained at the cost of low sensitivity and increased detector scatter. These limitations can be partially overcome by enlarging discrimination windows to include more low-energy events and by developing more efficient energydependent methods to correct for scatter radiation from all sources. The feasibility of multispectral scatter correction was assessed by decomposing response functions acquired in multiple energy windows into four basic components: object, collimator and detector scatter, and trues. The shape and intensity of these components are different and energy-dependent. They are shown to contribute to image formation in three ways: useful (true), potentially useful (detector scatter), and undesirable (object and collimator scatter) information to the image over the entire energy range. With the Sherbrooke animal PET system, restoration of detector scatter in every energy window would allow nearly 90% of all detected events to participate in image formation. These observations suggest that multispectral acquisition is a promising solution for increasing sensitivity in high resolution PET. This can be achieved without loss of image quality if energydependent methods are made available to preserve useful events as potentially useful events are restored and undesirable events removed.

The purpose of this paper is to present some useful methods for introductory analysis of variables and subsets in relation to PLS regression. We present here methods that are efficient in finding the appropriate variables or subset to use in the PLS regression. The general conclusion is that variable selection is important for successful analysis of chemometric data. An important aspect of the results presented is that lack of variable selection can spoil the PLS regression, and that cross-validation measures using a test set can show larger variation, when we use different subsets of X, than obtained by different methods. We also present an approach to orthogonal scatter correction. The procedures and comparisons are applied to industrial data.

Attenuation Correction is important among other corrections for quantitative Positron Emission Tomography (PET). A common method is to acquire transmission data using an external source from which attenuation correction factors are derived. The aim of this work was to compare different transmission methodologies for the microPET Focus 220 animal scanner in terms of accuracy, signal-to-noise and scatter. This study included experiments in coincidence mode with and without rod windowing, singles mode with two different energy sources ( 68 Ge and 57 Co) and post-injection transmission scanning. In addition, the effectiveness of transmission segmentation was investigated. The propagation of transmission bias and noise into the emission images was also examined. Singles transmission scanning resulted in substantially improved signal-to-noise compared with coincidence measurements. The 57 Co measurements provided attenuation coefficients close to the theoretical value for an energy window of 120-125 keV, while the 68 Ge single measurements were degraded due to scattering from the object. Transmission scatter correction improved the accuracy for a 10 cm phantom but over-corrected for a mouse phantom. 57 Co also resulted in low bias and noise in post-injection transmission scans for emission activities up to 20 MBq. Segmentation worked most reliably for transmission data acquired with 57 Co but the minor improvement in accuracy of attenuation coefficients and signal-to-noise did not justify its use, particularly for small subjects. The accuracy and signal-to-noise of activity concentration measurements reflected the accuracy and signal-to-noise of transmission measurements. We conclude that 57 Co singles transmission scanning is the most suitable method of attenuation correction on the microPET Focus 220 animal scanner. The microPET Focus 220 scanner is a high resolution PET system for imaging rodents and small primates. The images can be interpreted qualitatively by comparing radiotracer accumulation in target and reference regions of the body. In many experiments, however, there is either a need for absolute Manuscript received November 9, 2005.

We developed a unique method for estimating and compensating rigid-body translations and rotations from scatter and-attenuation-compensated projection data in iterative reconstruction when multiple projection angles are acquired at the same time. During reconstruction, both the non-attenuated and attenuated line-integrals are calculated. Their ratios are then multiplied to the scatter-corrected projection data to estimate scatter-and-attenuation-compensated projection data. At the end of each iteration, the sets of compensated projection data for the angles acquired at the same time are employed to calculate the center-of mass and the inertia tensor, which are used to estimate the location and orientation of the imaging object by the principle-axes method. The estimated motion is applied in the next iteration to reposition the estimated slices and attenuation map in the projector and back-projector to match the pose of the patient at time the projections were acquired. To evaluate our method, we simulated an acquisition of the MCAT phantom with a 3-head SPECT system and imaged the Data Spectrum anthropomorphic phantom on a 3-head IRIX SPECT system. In simulations the phantom translated and rotated by the same amount 9 times. A numerical projector modeling the motion, attenuation, and distance-dependent blurring was used to generate the projection data. Poisson noise was added and 30 noise-realizations were generated. In the experiment with the anthropomorphic phantom, four 360-degree acquisitions were performed with the phantom translated or rotated beforehand. A motion-present dataset was made by mixing the 4 acquisitions. For both the MCAT phantom simulations and anthropomorphic phantom experiment, the motion-present data were reconstructed with 10 iterations of the OSEM which estimates and corrects the motion as described above. Our method obtained visually artifact-free reconstructions, while the reconstruction with no motion correction showed severe artifacts. The motion estimated from our method was in good agreement with the motion simulated. We determined in MCAT simulated and actual phantom acquisitions that our data-driven approach was effective reducing motion artifacts.

An earlier localization ROC (LROC) study that found attenuation correction (AC) degraded the detection of solitary pulmonary nodules (SPN) in hybrid SPECT lung images had several potential shortcomings related to the simulation methods. We sought to address these issues with a revised LROC study. Clinical Tc-99m NeoTect scans acquired with a simultaneous transmission-emission protocol defined the normal cases in a single-slice LROC study. Abnormal cases contained a simulated 1-cm lung lesion. Four rescaled-block-iterative EM (RBI) reconstruction strategies applied: 1) AC, scatter correction (SC), and resolution compensation (RC); 2) AC only; 3) RC only; and 4) no corrections (NC). Images from these strategies underwent 3D Gaussian post-smoothing. Performances were defined by the average area under the LROC curve obtained from three human observers. The strategy ranking in order of decreasing performance was: 1) RBI with RC; 2) RBI with all corrections; 3) RBI with AC; and 4) RBI with no corrections. A multireader-multicase (MRMC) analysis only found significant patient and patient-strategy effects. The conflicting results concerning AC from this study and the previous one may revolve around lesion masking effects, which, by design, were not a factor in the current study. However, the simulation methods for Study I had several potential shortcomings. One of these was that the lesion density matched that of the lung background, so that the true soft-tissue nature of the SPN was not accounted for (lesion self-attenuation). Also, a parametric Poisson bootstrap had been applied to the patient data to generate unique noisy projections. With this bootstrap procedure, each bin value in the patient data set was treated as the mean of a Poisson distribution. Lastly, study I had questionable lesion placements as a result of some poor-quality transmission-map segmentations that were used to guide the placements.

Backprojected images offer compact and accurate storage of three-dimensional (3-D) positron emission tomography (PET) data and so are potentially very suited to high-resolution 3-D PET scanners. However, there are very few methods available for correcting backprojected images for the effects of scatter and random events. Scatter correction methods usually involve experimental measurement of scatter response functions or accurate simulations, and are thus limited by the accuracy of the model used. In contrast, the approach proposed here uniquely adapts a general form of a combined scatter and random response function. This method inherently does not rely upon accurate determination of the scatter and random response functions but does, however, rely upon knowledge of the attenuating object's outline. The technique is able to adapt to different imaging situations and account for detector scatter, and in particular is readily implemented in backprojection space. The method has been implemented for a small-volume HIDAC (II) PET scanner.

Transmission-dependent convolution subtraction (TDCS) is a promising technique in quantitative SPECT for subtracting the scatter components from emission images. Usually, a 20% photopeak energy window is used in SPECT acquisitions. To date, no investigation has assessed the effects of energy windows in the subtraction of scatter components from emission images with the TDCS technique. To evaluate the energy dependence of the TDCS technique, we analyzed photopeak energy windows of 5%, 10%, 15%, 20%, 25%, 30%, and 35% using 99m Tc radionuclide. The scatter fractions for a point source placed in a water phantom were estimated using the triple-energy-window (TEW) technique. These estimates were used to establish the parameters of the TDCS equation as a function of transmission. The estimated parameters were applied to the TDCS technique to subtract the scatter components from data of corresponding energy windows using nonuniform and uniform phantoms. All data were reconstructed with the OSEM algorithm. The energy window dependence of the TDCS technique was verified by comparing the coefficients of variance (COV) of the data from the uniform phantom of each energy window. Ten Poisson deviates were generated from each projection's data from the uniform phantom. The nonuniform phantom results showed that the estimated parameters effectively estimated the scatter component from the projection image for each energy window. The COV for the 5%,

Quantitative tissue classification using dual-energy CT has the potential to improve accuracy in radiation therapy dose planning as it provides more information about material composition of scanned objects than the currently used methods based on single-energy CT. One problem that hinders successful application of both single-and dualenergy CT is the presence of beam hardening and scatter artifacts in reconstructed data. Current pre-and post-correction methods used for image reconstruction often bias CT numbers and thus limit their applicability for quantitative tissue classification. Here we demonstrate simulation studies with a novel iterative algorithm that decomposes every soft tissue voxel into three base materials: water, protein and adipose. The results demonstrate that beam hardening artifacts can effectively be removed and accurate estimation of mass fractions of all base materials can be achieved. In the future, the algorithm may be developed further to include segmentation of soft and bone tissue and subsequent bone decomposition, extension from 2-D to 3-D and scatter correction.

we have implemented highly accurate Monte Carlo based scatter modeling (MCS) with 3-D ordered subsets expectation maximization (OSEM) reconstruction. The scatter i s included in the statistical model as an additive term and attenuation and detector response are included in the forward/backprojector. In the present implementation of MCS, a simple multiple window-based estimate is used for the initial iterations and in the later iterations the Monte Carlo estimate i s used for several iterations before it is updated. For I-131, MCS was evaluated and compared with triple energy window (TEW) scatter compensation using simulation studies of a mathematical phantom and a clinically realistic voxel-phantom. Even after just two Monte Carlo runs, excellent agreement was found between the MCS estimate and the true scatter distribution. Accuracy and noise of the reconstructed images were superior with MCS compared to TEW. However, the improvement was not large, and in some cases may not justify the large computational requirements of MCS. Finally clinical application of MCS was demonstrated by applying the method to a radioimmunotherapy (RIT) patient study.

Epidepride labelled with iodine-123 is a suitable probe for the in vivo imaging of striatal and extrastriatal dopamine D 2 receptors using single-photon emission tomography (SPET). Recently, this molecule has also been labelled with carbon-11. The goal of this work was to develop a method allowing the in vivo quantification of radioactivity uptake in baboon brain using SPET and to validate it using positron emission tomography (PET). SPET studies were performed in Papio anubis baboons using 123 I-epidepride. Emission and transmission measurements were acquired on a dual-headed system with variable head angulation and low-energy ultra-high resolution (LEUHR) collimation. The imaging protocol consisted of one transmission measurement (24 min, heads at 90°), obtained with two sliding line sources of gadolinium-153 prior to injection of 0.21-0.46 GBq of 123 I-epidepride, and 12 emission measurements starting 5 min post injection. For scatter correction (SC) we used a dual-window method adapted to 123 I. Collimator blurring correction (CBC) was done by deconvolution in Fourier space and attenuation correction (AT) was applied on a preliminary (CBC) filtered back-projection reconstruction using 12 iterations of a preconditioned, regularized minimal residual algorithm. For each reconstruction, a calibration factor was derived from a uniform cylinder filled with a 123 I solution of a known radioactivity concentration. Calibration and baboon images were systematically built with the same reconstruction parameters. Uncorrected (UNC) and (AT), (SC+AT) and (SC+CBC+AT) corrected images were compared. PET acquisitions using 0.11-0.44 GBq of 11 C-epidepride were performed on the same baboons and used as a reference. The radioactive concentrations expressed in percent of the injected dose per 100 ml (%ID/100 ml) obtained after (SC+CBC+AT) in SPET are in good agreement with those obtained with PET and 11 Cepidepride. A method for the in vivo absolute quantitation of 123 I-epidepride uptake using SPET has been developed which can be directly applied to other 123 I-labelled molecules used in the study of the dopamine system. Further work will consist in using PET to model the radioligandreceptor interactions and to derive a simplified model applicable in SPET.

Cardiac SPECT images are degraded by photons scattered in the thorax. Accurate correction for scatter is complicated by the nonuniform density and varied sizes of thoraxes and by the additional attenuation and scatter caused by female patients' breasts. Monte Carlo simulation is a general and accurate method for detailed modeling of scatter. Hence, for 99m Tc we compared statistical reconstruction based on Monte Carlo modeling of scatter with statistical reconstruction that incorporates the more commonly used triple-energy-window scatter correction. Both of these scatter correction methods were used in conjunction with attenuation correction and resolution recovery. Methods: Simultaneous attenuation, detector response, and Monte Carlo-based scatter correction were implemented via the dual-matrix orderedsubset expectation maximization algorithm with a Monte Carlo simulator as part of the forward projector (ADS-MC). ADS-MC was compared to (i) ordered-subset expectation maximization with attenuation correction and with detector response modeling (AD); (ii) like (i) but with scatter correction added using the tripleenergy-window method (ADS-TEW). A dual-detector SPECT system equipped with 2 153 Gd scanning line sources was used for acquiring 99m Tc emission data and attenuation maps. Four clinically realistic phantom configurations (a large thorax and a small thorax, each with and without breasts) with a cardiac insert containing 2 cold defects were used to evaluate the proposed reconstruction algorithms. In these phantom configurations, we compared the performance of the algorithms in terms of noise properties, contrast-to-noise ratios, contrast separability of cold defects, and robustness to anatomic variation. Results: Noise was found to be approximately 14% lower in the ADS-MC images than in the ADS-TEW and AD images. Typically, the contrast obtained with the ADS-MC algorithm was 10%-20% higher than that obtained with the other 2 methods. Furthermore, compared with the other 2 algorithms, the ADS-MC method was less sensitive to anatomic variations. Conclusion: Our results indicate that the imaging performance of 99m Tc SPECT can be improved more by Monte Carlo-based scatter correction than by window-based scatter correction.

It is commonly understood that scattered radiation in X-ray computed tomography (CT) reduces the CT number and degrades the quality of reconstructed images. This effect is more pronounced in multi detector CT scanners with extended detector aperture mostly using cone-beam configurations, which are much less immune to scatter than fan-beam and single-slice CT scanners. To perform accurate scatter correction, it is essential to characterize scattered radiation in Volumetric CT. As characterization of scattered radiation behavior using experimental measurement is a difficult and time consuming approach, Monte Carlo simulation can be an ideal method. In this study we used Geant4-based simulation package, GATE, to model x-ray photon interactions in the phantom and detector. The Monte Carlo simulation was validated through comparison with experimental measurement data. Thereafter, the effect of different parameters such as tube voltage and phantom material on the scatter profile and Scatter to Primary Ratio (SPR) was calculated. We also compared the simulated SPR curves with experimental data which was measured with array blocker method. The experimental technique assumed to be the gold

Cupping and streak artifacts caused by the detection of scattered photons may severely degrade the quantitative accuracy of cone-beam X-ray computed tomography (CT) images. In order to overcome this problem, we propose and validate the following iterative scatter artifact reduction scheme. First, an initial image is reconstructed from the scatter-contaminated projections. Next, the scatter component of the projections is estimated from the initial reconstruction by a Monte Carlo (MC) simulation. The estimate obtained is then utilized during the reconstruction of a scatter-corrected image. The last two steps are repeated until an adequate correction is obtained. The estimation of the noisefree scatter projections in this scheme is accelerated in the following way: first, a rapid (i.e., based on a low number of simulated photon tracks) MC simulation is executed. The noisy result of this simulation is de-noised by a three-dimensional fitting of Gaussian basis functions. We demonstrate that, compared to plain MC, this method shortens the required simulation time by three to four orders of magnitude. Using simulated projections of a small animal phantom, we show that one cycle of the scatter correction scheme is sufficient to produce reconstructed images that barely differ from the reconstructions of scatter-free projections. The reconstructions of data acquired with a charge-coupled device based micro-CT scanner demonstrate a nearly complete removal of the scatter-induced cupping artifact. Quantitative errors in a water phantom are reduced from around 12% for reconstructions without the scatter correction to 1% after the proposed scatter correction has been applied. In conclusion, a general, accurate, and efficient scatter correction algorithm is developed that requires no mechanical modifications of the scanning equipment and results in only a moderate increase in the total reconstruction time.

Scattering effect is a really common physical phenomenon during near‐infrared analysis. It is an undesired variation in the spectral data due to a deviation of light from a straight trajectory into different paths. The nonlinearities introduced can be handled by using spectral preprocessing techniques. The situation is completely different when the parameter of interest is physical by nature, such as ash content, in this case removing the physical artifacts of scattering would be negative for the final model. In this study, we have decided to investigate the ash content parameter trying to figure out if the information useful for its prediction is related to the scattering effects, the chemical features, or a mixture of them. To this aim, two near‐infrared spectral datasets were taken into consideration: woodchip for energy sector and pellet samples for feed sector. A new regression model (CORR‐PLS) was developed by including principal components analysis scores and extended multipl...

Objective We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body 18 F-FDG PET imaging. Methods Two-and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body 18 F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively. The images generated by the proposed approach were assessed using various evaluation metrics, including the root-mean-squared-error (RMSE) and absolute relative error (ARE %) using CT-based attenuation and scatter-corrected (CTAC) PET images as reference. PET image quantification variability was also assessed through voxel-wise standardized uptake value (SUV) bias calculation in different regions of the body (head, neck, chest, liver-lung, abdomen and pelvis). Results Our proposed attenuation and scatter correction (Deep-JASC) algorithm provided good image quality, comparable with those produced by CTAC. Across the 150 patients of the independent external validation set, the voxel-wise REs (%) were − 1.72 ± 4.22%, 3.75 ± 6.91% and − 3.08 ± 5.64 for DL-2DS, DL-3DS and DL-3DP, respectively. Overall, the DL-2DS approach led to superior performance compared with the other two 3D approaches. The brain and neck regions had the highest and lowest RMSE values between Deep-JASC and CTAC images, respectively. However, the largest ARE was observed in the chest (15.16 This article is part of the Topical Collection on Advanced Image Analyses (Radiomics and Artificial Intelligence)

The nano-era of semiconductor electronics introduces the necessity of simulation methods which describe the electron transport in ultra-small devices in a mixed mode where quantumcoherent processes are considered along with the de-coherence processes of scattering. The latter can be conveniently described in the Wigner picture of quantum mechanics, however the coherent counterpart gives rise to heavy numerical problems. We propose a scheme which combines the advantages of the Wigner function with the Green's function picture which is numerically efficient in coherent cases. An equation accounting for the scattering corrections to the coherent Wigner function is derived theoretically and a Monte Carlo algorithm for calculating these corrections is developed and implemented. The implementation is deployed on the SEE-GRID to facilitate the swift acquisition of results. Simulation results are presented as a final point.

We are investigating methods of scatter correction that use multiple (typically, 6-15) energy bins for scatter correction in single photon imaging. We have previously reported preliminary results of this work with simple phantoms. In this article, we present new experimental results using the Rollo phantom, a complex phantom designed for evaluation of quantitative imaging techniques. We have refined our correction techniques by allowing the use of Poisson weighting and by developing a technique for progressive basis function refinement. We have studied a new class of methods, the "minimum risk" estimators, which are specifically designed to minimize the mean-square error (MSE) of primary and scatter estimates (much like the goal of the Wiener filter, but in the energy domain). The performance of minimum-risk estimators and our earlier constrained minimization techniques both improve on that of simple deconvolution, particularly with respect to noise sensitivity. We have applied these techniques to the removal of scatter from images of the Rollo phantom filled with Tc-99m, 1-131, and T1-201; studies with variable-depth scatterers and other isotopes are currently underway.

A series of 2D and 3D count rate measurements have been carried out on the Advance PET system. The measurements include: NEMA standard protocols; simultaneous imaging of two small vials containing [O-15lwater and [F-18]; a cardiac insert placed in a water filled elliptical tank; two different head sized cylindrical tanks; and a Hoffman 3D phantom. The data were processed with and without dead time and scatter corrections. Plots were made of the total count rate, randoms, trues + scatter, scatter corrected trues, and noise equivalent count rate as a function of total activity in the machine and as the pCi/cc in the phantoms. The accuracy of deadtime corrections was also measured. In 2D mode, the NEMA standard protocol resulted in maximum 'trues' count rates of 540,000 cps in high sensitivity mode. In 3D mode the head sized cylindrical phantoms yielded a maximum trues rate of approximately 950,000 cps. Recovery of the water half-life was accurate with up to 50 mCi for the cardiac insert in 2D mode.

ransaxial field of view Performance measurements of the General Electric ADVANCE Positron Emission Tomograph operating with the septa retracted (3D mode) were made. All reconstructions were performed with the GE ADVANCE 3D package. Performance tests were carried out with: the NEMA phantoms; a 3D Hoffman phantom; a Data Spectrum torso phantom with lung and cardiac inserts; and the "Utah" 3D evaluation phantom. Data collected included: transaxial and axial resolution, uniformity, recovery coefficients, count rate performance, dead tiime accuracy, and effect of scatter correction.

Cardiac SPECT images are degraded by photons scattered in the thorax. Accurate correction for scatter is complicated by the nonuniform density and varied sizes of thoraxes and by the additional attenuation and scatter caused by female patients' breasts. Monte Carlo simulation is a general and accurate method for detailed modeling of scatter. Hence, for 99m Tc we compared statistical reconstruction based on Monte Carlo modeling of scatter with statistical reconstruction that incorporates the more commonly used triple-energy-window scatter correction. Both of these scatter correction methods were used in conjunction with attenuation correction and resolution recovery. Methods: Simultaneous attenuation, detector response, and Monte Carlo-based scatter correction were implemented via the dual-matrix orderedsubset expectation maximization algorithm with a Monte Carlo simulator as part of the forward projector (ADS-MC). ADS-MC was compared to (i) ordered-subset expectation maximization with attenuation correction and with detector response modeling (AD); (ii) like (i) but with scatter correction added using the tripleenergy-window method (ADS-TEW). A dual-detector SPECT system equipped with 2 153 Gd scanning line sources was used for acquiring 99m Tc emission data and attenuation maps. Four clinically realistic phantom configurations (a large thorax and a small thorax, each with and without breasts) with a cardiac insert containing 2 cold defects were used to evaluate the proposed reconstruction algorithms. In these phantom configurations, we compared the performance of the algorithms in terms of noise properties, contrast-to-noise ratios, contrast separability of cold defects, and robustness to anatomic variation. Results: Noise was found to be approximately 14% lower in the ADS-MC images than in the ADS-TEW and AD images. Typically, the contrast obtained with the ADS-MC algorithm was 10%-20% higher than that obtained with the other 2 methods. Furthermore, compared with the other 2 algorithms, the ADS-MC method was less sensitive to anatomic variations. Conclusion: Our results indicate that the imaging performance of 99m Tc SPECT can be improved more by Monte Carlo-based scatter correction than by window-based scatter correction.

Conclusion DD allows the acquisition of CT images at different kV settings with only one calibration curve in the planning system, with a minimum impact in dose calculations. However it needs matching with the original FBP images for volume delineation due to the lower image quality. Consequently Direct Density™ is accurate enough to be introduced in clinical routine. EP-2040 IDose4 algorithm for radiotherapy planning process: how reduce the dose without image quality loss

The UK national standards laboratory, the National Physical Laboratory (NPL), provides an extensive range of facilities for measurements on neutron sources and neutron-sensitive devices. This paper describes recent improvements and extensions to the neutron standards. Correction factors used in source strength measurements have been improved, as have the scatter corrections used in monoenergetic and source-based irradiations. Characterisation of the thermal field facility has been improved by activation measurements. Experimental facilities developed recently include a system for measuring personal dosemeter responses at several energies simultaneously, and a neutron source tailored to simulate typical workplace fields.

There are various sources of errors from the measurements of optical parameters using a radiometer, which can be classified as mode of deployment, instrument and environment. The errors from the deployment are primarily from the ship and superstructure shadows. Instrument could be a source of error arising from its self-shadow, drift in the calibration and temperature effects. There could be large errors, which at times may be unavoidable to environment factors such as wave focusing at the surface layers, sea state conditions which may affect the tilt of the instrument, atmospheric conditions such as cloud cover, solar elevation, wind and rain. Radiometric optical data in water could also get affected due to Raman scattering and fluorescence effects. Here we discuss the above sources of errors and how they could be minimized. From the measurements carried out in the coastal waters off Goa and Arabian Sea using the hype-spectral radiometer, we propose simple protocol to measure the data and also screen the erroneous data measured from the radiometer.

Measurements from the MF spaced antenna mode radar at Scott Base (78°S, 167°E) include an estimate of the autocorrelation time scale (T0.5) of the scatterers, corrected for advection by the mean wind. Summer observations (December 1983) show a semidiurnal variation of T0.5. At heights of 87–95 km the minimum values of T0.5 occur when the zonal component of the semidiurnal tide is at its westward maximum. If it is assumed that decreasing values of T0.5 are associated with increasing turbulence, then these results are consistent with those of Balsley et al. (1983), who proposed that enhanced turbulence is generated in summer by low‐frequency gravity waves and tidal components above the polar mesopause.

accuracy of the reconstructed image depends strongly on the accuracy of the model of the ima.ge formation process (e.g., [1]-[7]). This dependency calls for modeling of the complete two-dimensional (2-D) point !spread function of the imaging system (e.g., [5], [S]-[Il]), and is called fully threedimensional (3-D) reconstruction (Fig. 1). Because often the Manuscript

Quantitative analysis can improve the sensitivity and specificity of single photon emission tomography (SPET) procedures, as well as reduce inter-and intraobserver variabilities. Quantification of the radioactivity distribution is the ultimate goal of SPET. In this review we consider the basic requirements for an optimum three-dimensional reconstruction of the radionuclide distribution to enable quantification. Attenuation and scatter correction as well as varying resolution are the major problems. In the older SPET systems quantification was hampered by the lack of system sensitivity and sufficient computer power. Therefore, the imaging system was often assumed to be shift invariant and linear and the attenuation throughout the object uniform. More sophisticated solutions have been proposed and with more or less success implemented, but not for application in daily practice. Knowledge (measurement) of the attenuation is often required. New generation SPET systems employing multi-detectors and super minicomputers will ease the implementation of these solutions.

A 5-fold increase of the half-life of the microbubbles was obtained after coating them with PAH. The ability of the microbubbles to protect pDNA against nuclease cleavage was tested using gel electrophoresis. The uncoated microbubbles were not able to protect pDNA from degradation by DNase I. Oppositely the PAH coated microbubbles were able to prevent degradation.

Digital flat-panel-based volume CT (VCT) represents a unique design capable of ultra-high spatial resolution, direct volumetric imaging, and dynamic CT scanning. This innovation, when fully developed, has the promise of opening a unique window on human anatomy and physiology. For example, the volumetric coverage offered by this technology enables us to observe the perfusion of an entire organ, such as the brain, liver, or kidney, tomographically (e.g., after a transplant or ischemic event). By virtue of its higher resolution, one can directly visualize the trabecular structure of bone. This paper describes the basic design architecture of VCT. Three key technical challenges, viz., scatter correction, dynamic range extension, and temporal resolution improvement, must be addressed for successful implementation of a VCT scanner. How these issues are solved in a VCT prototype and the modifications necessary to enable ultra-high resolution volumetric scanning are described. The fundamental principles of scatter correction and dose reduction are illustrated with the help of an actual prototype. The image quality metrics of this prototype are characterized and compared with a multi-detector CT (MDCT).

Background: Several descriptors are used to characterize the dosimetric parameters of a photon beam through an attenuator. This study evaluates these descriptors analytically through various thicknesses of Gamma Putty. Specifically, we measure percent ionization depth doses as a function of depth and field size, and fit three models to the data. Materials and Methods: Measurements of percent ionization at various depths along the central axis were generated from 6 MV and 18 MV photon beams at a source-axis distance of 100 cm with an ionization in solid water phantom. We fit analytic models to the data to determine linear attenuation, beam hardening, beam quality, and electron contamination. Results: We report best-fit parameters for all the analytical models. All models yielded a root mean square (RMS) error of less than 1% with respect to the data. At depths below 5cm in the phantom, the largest attenuation coefficients (μ) were observed for the 6 MV beam, regardless of Gamma Putty thickness. Also, the smallest field sizes (4×4 and 5×5 cm 2) have the largest attenuation coefficients at these depths, for both beam energies. At a depth of 10 cm, the variation in μ was negligible for both beam energies. Conclusions: By fitting parametric models to axial ionization profiles, it is possible to characterize the dosimetric parameters of any attenuator as a function of thickness and field size, without knowing the precise spectral distribution of the beam. Parameters such as attenuation coefficients, beam hardening, and electron contamination can then be calculated accurately for any combination of field size and attenuator thickness.

Our purpose was to investigate whether tube potential in contrast-enhanced computed tomography (CT) affects body composition analysis. Images from dual-source, dual-energy CT from the abdomen with intravenous contrast media administration were used. A total of 17 patients (11 women, mean age 52) with a mean body mass index of 20.8 kg/cm were included. Simultaneously acquired images with a tube voltage of 80 kV and 140 kV were compared. Body composition was analyzed on a single slice at the L3 level. Parameters evaluated included muscle and fat attenuation (Hounsfield units [HU]), skeletal muscle index (cm/m), muscle area (cm), and steatotic muscle area (cm). Significant differences between 80 kV and 140 kV series were compared using the paired Student&#39;s t test. Tube potential affected muscle attenuation with an average difference of 17% between 80 kV and 140 kV series (48 HU versus 41 HU, P &lt; 0.01), fat attenuation (-84 HU versus -69 HU, P &lt; 0.01), skeletal muscle index of...

Partial least-squares (PLS) regression was used to generate various models for the determination of both the protein and the ash contents of wheat flours by using spectroscopic data in the mid-infrared region obtained with a horizontal attenuated total reflectance (HATR) accessory. One hundred samples of wheat flour were used as purchased in the market: 55 for constructing the calibration model and 45 as external samples. The protein content varied between 8.85 and 13.23% and the ash content, between 0.330 and 1.287%, as determined by reference methods. Raw spectra and those corrected by multiplicative signal correction (MSC), first and second derivative spectra, were used as data for building the models. Different pre-treatments, such as mean centered and/or variance scaled (VS) methods, were tested and compared. Very good models were built as judged by the correlation coefficients (R 2), root mean square error of calibration (RMSEC), root mean square error of validation (RMSEV) and root mean square error of prediction (RMSEP) that were obtained. Best results were achieved with MSC treated spectra.