Scatter Correction Method Research Articles

A rapid quality grade discrimination method for Gastrodia elata powderusing ATR-FTIR and chemometrics

Gastrodia elata is an obligate fungal symbiont used in traditional Chinese medicine. There are currently 4 grades of the plant based on the “Commodity Specification Standard of 76 Kinds of Medicinal Materials”. The traditional discrimination methods for determining the medicinal grade of G. elata powders are complex and time-consuming which are not suitable for rapid analysis. We developed a rapid analysis method for this plant using attenuated total reflection and Fourier-transform infrared spectroscopy (ATR-FTIR) together with machine learning algorithms. The original spectroscopic data was first pre-treated using the multiplicative scatter correction (MSC) method and 4 principal components were extracted using extremely randomized trees (Extra-trees) and principal component analysis (PCA) algorithms, and different kinds of classification models were established. We found that multilayer perceptron classifier (MLPC) modeling was superior to support vector machine (SVM) and resulted in validation and prediction accuracies of 99.17% and 100%, respectively and a modeling time of 2.48 s. The methods established from the current study can rapidly and effectively distinguish the 4 different types of G. elata powders and thus provides a platform for rapid quality inspection.

Simultaneous multi-nuclide imaging via double-photon coincidence method with parallel hole collimators

Multi-tracer imaging can provide useful information in the definitive diagnosis and research of medical, biological, and pharmaceutical sciences. Single-photon emission computed tomography (SPECT) is one of the nuclear medicine imaging modalities widely used for diagnosis or medical research and has a multi-tracer imaging capability. One of the drawbacks of multi-tracer imaging is crosstalk from other gamma rays, which affects the reconstructed image. Scattering correction methods, such as the dual- and triple-energy window methods, are used for conventional SPECT imaging to reduce the background caused by the crosstalk. This study proposes another crosstalk reduction method. Some nuclides emit two or more gamma rays through intermediate levels. Thus, detecting these gamma rays with the coincidence method allows us to distinguish a true gamma ray signal and a background signal. The nuclide position can be estimated at the intersection of two gamma rays using collimators. We demonstrate herein simultaneous 111In and 177Lu imaging via the double-photon coincidence method using GAGG detectors and parallel hole collimators. The double-photon coincidence method greatly reduces the background caused by other gamma rays and offers higher-quality images than does conventional imaging.

Evaluation of single scattering correction method in compton imaging system

Compton imaging is a powerful imaging method used to acquire the distribution of gamma-ray emitting radioactive sources. It can be used for various applications, including homeland security and medical imaging. Similar to other modalities of radiation imaging, scattering is a source of noise in the reconstructed image. The correction of the scatter effect is important for more quantitatively accurate imaging. In this study, a single scattering correction was conducted by setting arbitrary scattering points on the attenuating material. A Monte Carlo simulation was conducted to observe the effect of scattering on reconstructed images, and an experiment was conducted to validate the proposed method using Geant4. The results showed that the method effectively removed the noise on the reconstructed image while not impairing the image quality.

A unified scatter rejection and correction method for cone beam computed tomography.

Scattered radiation is a major cause of image quality degradation in flat panel detector-based cone beam CT (CBCT). While recently introduced 2D antiscatter grids reject the majority of scatter fluence, the small percentage of scatter fluence still transmitted to the detector remains a major challenge for implementation of quantitative imaging techniques such as dual energy imaging in CBCT. Additionally, this residual scatter is also a major source of grid-induced artifacts, which impedes implementation of 2D grids in CBCT. We therefore present a new method to achieve both robust scatter rejection and residual scatter correction using a 2D antiscatter grid; in doing so, we expand the role of 2D grids from mere scatter rejection devices to scatter measurement devices. In our method, the radiopaque septa of the 2D grid emulate a micro array of beam-stops placed on the detector which introduce spatially periodic septal shadows. By selecting sufficiently thin grid septa, the primary intensity can be reduced while preserving the uniformity of scatter intensity. This enables us to correlate the modulated pixel signal intensity in septal shadows with local scatter intensity. Our method then exploits this correlation to measure and remove residual scatter intensity from projections. No assumptions are made about the object being imaged. We refer to this as Grid-based Scatter Sampling (GSS). In this work, we evaluate the principle of signal modulation with grid septa, the accuracy of scatter estimates, and the effect of the GSS method on image quality using simulations and measurements. We also implement the GSS method experimentally using a 2D grid prototype. Our results demonstrate that the GSS method increased CT number accuracy and reduced image artifacts associated with scatter. With 2D grid and residual scatter correction, HU nonuniformity was reduced from 65HU to 30HU in pelvis sized phantoms, and HU variations due to change in phantom size were reduced from 59HU to 20HU, when compared to use of only a 2D grid. With residual scatter correction via GSS method, grid-induced ring artifacts were suppressed, leading to a 41% reduction in noise. The shape of the modulation transfer function (MTF) was preserved before and after suppression of ring artifacts. Our grid-based scatter sampling method enables utilization of a 2D grid as a scatter measurement and correction device. This method significantly improves quantitative accuracy in CBCT, further reducing the image quality gap between CBCT and multi-detector CT. By correcting residual scatter with the proposed method, grid-induced line artifacts in projections and associated ring artifacts in CBCT images were also suppressed with no compromise of spatial resolution.

Estimation of Starch Hydrolysis in Sweet Potato (Beni Haruka) Based on Storage Period Using Nondestructive Near-Infrared Spectrometry

Sweet potatoes are a substantial source of nutrition and can be added to processed foods in the form of paste. The moisture and starch contents of these potatoes affect the physicochemical properties of sweet potato paste. In this study, the changes in the moisture, starch, and α-amylase content of sweet potatoes were measured for eight weeks after harvest. Using nondestructive near-infrared analyses and chemometric models, the moisture and starch contents were predicted. The partial least squares (PLS) method was used for prediction, while linear discriminant analysis (LDA) was used for discrimination. To increase the accuracy of the model, the near-infrared spectrum was preprocessed using the Savitzky–Golay derivative (S–G), standard normal variate (SNV), and multiplicative scattering correction methods. When applying PLS to the moisture content, the best calibration model accuracy was obtained using the S–G preprocessed spectrum. Furthermore, the best calibration model accuracy for starch content was obtained using the SNV preprocessed spectrum. The moisture and starch contents were categorized into five classes for LDA, with results indicating that the internal quality of sweet potatoes can be predicted and classified using chemometric models through nondestructive detection.

Improved prediction of protein content in wheat kernels with a fusion of scatter correction methods in NIR data modelling

The study aims to test the hypothesis that modelling of near-infrared (NIR) spectroscopic data based on a single scatter correction technique is sub-optimal. Better predictive performance of the multivariate analysis method can be obtained when the information from differently scatter corrected data is jointly used. To demonstrate it, an open-source NIR spectroscopy data set related to protein prediction in wheat kernels was used. Two different pre-processing fusion approaches i.e., sequential and parallel fusion, were used for fusing the complementary information from four different scatter correction techniques, namely standard normal variate (SNV), variable sorting for normalisation (VSN), 2nd derivative, and multiplicative scatter correction (MSC). As a comparison, partial least-squares regression (PLSR) was performed on the SNV pre-processed data. The results showed that fusion of scatter correction can improve the predictive performance of NIR spectroscopic models. The results revealed that both sequential and parallel fusion approaches improved the predictive performance compared to the PLSR performed using a single scatter correction technique. The R2p was improved by up to 3% and the RMSEP was reduced by up to 13% compared to the results obtained with conventional PLSR model developed with a single scatter correction technique.

Non-destructive determination of fatty acid composition of in-shell and shelled almonds using handheld NIRS sensors

One of the major compounds in almond kernels, which determines their nutritional quality, are lipids. The aim of this research was to determine the fatty acid profile in intact in-shell and shelled almonds (145 samples) using two new generation handheld near infrared spectroscopy (NIRS) sensors, of different optical design and technical specifications, adapted for in situ analysis in different stages in the food supply chain: in the industry after harvest, at the reception points and during postharvest storage. For both instruments, two procedures for taking near infrared (NIR) spectra were tested: (1) static, where point spectral readings were taken of almonds placed on trays; (2) dynamic, where spectra were taken by scanning the entire trays. Modified partial least squares (MPLS) regression models were developed using NIR spectra with different combinations of signal pre-treatments — derivative and scatter correction methods. The residual predictive deviation for cross validation (RPDcv) of the best models developed for the prediction of palmitic, stearic, oleic, and linoleic acids using shelled almonds were 2.40, 2.16, 3.98, and 3.77, respectively, and 1.73, 1.73, 2.02, and 2.11 for the in-shell almonds. These results confirm the feasibility of NIRS technology to measure the fatty acid profile in in-shell and shelled almonds. A comparison between the presentation mode (in-shell or shelled) and analysis mode (static or dynamic) showed that the best results were obtained for shelled almonds analysed in dynamic mode.

Improvement of Cold Artifacts in Body Trunk 18F-FDG PET/CT by Absolute-single scatter simulation: Validation in an Out-of-body High-accumulation Phantom

This study aimed to verify whether cold artifacts caused by the gap state between attenuation correction computed tomography (ACCT) and positron emission tomography (PET) data (so-called hot-in-air (HIA) state) in body trunk PET/computer tomography (CT) examinations can be improved by the Absolute-single scatter simulation (SSS), which is a scatter correction method in a phantom experiment using the high-accumulation syringe of out-of-body phantom. PET imaging profile curves in the HIA state were evaluated using a high-accumulation syringe that simulated a urinary tract pouch encapsulated with 18F-FDG solution. The hot syringe-to-background ratio (HBR) of the syringe was changed to 5, 7, and 10. Moreover, PET image quality evaluation of the HIA state was performed with a syringe placed on the top of a NEMA IEC body phantom. Six spheres (10-37 mm in diameter) were placed inside the phantom and filled with 18F-FDG solution with a sphere-to-background ratio of 4. The evaluation items of image quality were N10 mm, QH, 10 mm / N10 mm, and recovery coefficient (RC). The image quality tended to deteriorate as the HBR of the syringe increased in the relative-SSS, while the effect was small in the Absolute-SSS and the lowest at HBR 10. The RC10 mm of HBR 5 was 0.33 for the Relative-SSS, which was below the criterion for the Relative-SSS, but was 0.5 for the Absolute-SSS, which met the criterion. Absolute-SSS significantly improved cold artifacts caused by HIA states on body trunk PET/CT examinations, suggesting that it is highly useful both visually and quantitatively.

Optimization of scatter estimation window setting for quantitative analysis in 111 In-pentetreotide single photon emission computed tomography imaging.

The aim of this study was to validate the optimal scatter correction method and scatter estimation window setting in terms of image quality and quantitative accuracy for quantitative indium-111 (111In)-pentetreotide SPECT imaging. We used a positron emission tomography/computed tomography (PET/CT) phantom to validate image quality and quantitative accuracy, and the SPECT images were acquired by the multi-energy window (MEW) method. The scatter estimation was performed using four kinds of energy windows (MEW1, MEW2, MEW3, and MEW4). Scatter correction was also performed using a dual-energy window (DEW) for comparison with MEWs. Image quality was assessed using percent contrast (% contrast) and background variability, and quantitative accuracy was assessed using the mean standardized uptake value (SUVmean) with hot spheres. In the quantification, all MEW settings approached the theoretical SUVmean (MEW1, 0.99±0.06; MEW2, 0.99±0.05; MEW3, 1.00±0.08; MEW4, 0.97±0.12) in contrast to DEW (0.88±0.05). The SUVmean value for scatter correction of both photopeaks for a 28 mm sphere showed the smallest difference from the theoretical value. The scatter correction method that gave optimal image quality and quantitative accuracy was MEW3 with two 20% energy windows (one over each photopeak) and four adjacent 3% scatter estimation windows (one on each side of the two photopeaks).

Contrast optimization using triple energy window scatter correction method for In-111 SPECT imaging: A SIMIND Monte Carlo study

Introduction: Detection of scattered photons in photo-peak window degrades image contrast and quantitative accuracy of single-photon emission computed tomography (SPECT) imaging. Increases image contrast lead to significant improvement of image quality. The triple energy window (TEW) method, which has developed to eliminate the counts of scatter photons in measured counts, was applied to I-111 SPECT study and its effect was examined in a simulation study. Materials and method: The Siemens SYMBIA gamma camera equipped with a medium energy (ME) collimator was simulated by the Simulating Medical Imaging Nuclear Detectors (SIMIND) program. We used the SIMIND Monte Carlo program to generate the I-111 SPECT projection data of the Jaszczak phantom. The phantom consists of six spheres with different diameters (9.5, 12.7, 19.1, 15.9, 25.4, and 31.8 mm) which are used to evaluate the image contrast. Geometric, scatter and penetration fraction and also, point-spread functions (PSFs) and contrast curves were drawn and compared. Results: Results showed that 171keV photo-peak compared to 245keV gave the best results with a ME collimator when the TEW scatter correction method was applied. This can be explained by the large amount of collimator scatter and penetration from the photo-peak and by the collimator for 245 photo-peak window. Conclusion: With TEW scatter correction method, it is better to use a 171keV photo-peak window because of the better spatial resolution and image contrast.

Quantitative 166Ho-microspheres SPECT derived from a dual-isotope acquisition with 99mTc-colloid is clinically feasible

PurposeAccurate dosimetry is essential in radioembolization. To this purpose, an automatic protocol for healthy liver dosimetry based on dual isotope (DI) SPECT imaging, combining holmium-166 (166Ho)-microspheres, and technetium-99 m (99mTc)-colloid was developed: 166Ho-microspheres used as scout and therapeutic particles, and 99mTc-colloid to identify the healthy liver. DI SPECT allows for an automatic and accurate estimation of absorbed doses, introducing true personalized dosimetry. However, photon crosstalk between isotopes can compromise image quality. This study investigates the effect of 99mTc downscatter on 166Ho dosimetry, by comparing 166Ho-SPECT reconstructions of patient scans acquired before (166Ho-only) and after additional administration of 99mTc-colloid (166Ho-DI).MethodsThe 166Ho-only and 166Ho-DI scans were performed in short succession by injecting 99mTc-colloid on the scanner table. To compensate for 99mTc downscatter, its influence was accounted for in the DI image reconstruction using energy window-based scatter correction methods. The qualitative assessment was performed by independent blinded comparison by two nuclear medicine physicians assessing 65 pairs of SPECT/CT. Inter-observer agreement was tested by Cohen’s kappa coefficient. For the quantitative analysis, two volumes of interest within the liver, VOITUMOR, and VOIHEALTHY were manually delineated on the 166Ho-only reconstruction and transferred to the co-registered 166Ho-DI reconstruction. Absorbed dose within the resulting VOIs, and in the lungs (VOILUNGS), was calculated based on the administered therapeutic activity.ResultsThe qualitative assessment showed no distinct clinical preference for either 166Ho-only or 166Ho-DI SPECT (kappa = 0.093). Quantitative analysis indicated that the mean absorbed dose difference between 166Ho-DI and 166Ho-only was − 2.00 ± 2.84 Gy (median 27 Gy; p value < 0.00001), − 5.27 ± 8.99 Gy (median 116 Gy; p value = 0.00035), and 0.80 ± 1.08 Gy (median 3 Gy; p value < 0.00001) for VOIHEALTHY, VOITUMOR, and VOILUNGS, respectively. The corresponding Pearson’s correlation coefficient between 166Ho-only and 166Ho-DI for absorbed dose was 0.97, 0.99, and 0.82, respectively.ConclusionThe DI protocol enables automatic dosimetry with undiminished image quality and accuracy.Clinical trialsThe clinical study mentioned is registered with Clinicaltrials.gov (NCT02067988) on 20 February 2014.

Alternative particle compensation techniques for online water quality monitoring using UV–Vis spectrophotometer

Particles in the water can significantly affect UV–Vis absorption measurements. There is a need for the water industry to develop a reliable technique to eliminate particle impact on on-line water quality monitoring using UV–Vis spectroscopy. This study aims to develop and use digital techniques for particle compensation: single wavelength compensation, linear regression compensation and multiplicative scatter correction method for on-line UV–Vis spectrophotometers. Water quality data were collected from three selected water sources in water treatment plants which represent different water qualities in terms of particles and organic matters. UV254 measurements were determined with these three software compensation techniques in comparison with the proprietary instrument built-in compensation algorithm using Bland-Altman analysis. Linear correction methods were found to be able to adjust the three compensation techniques to achieve acceptable compensated UV254 results, particularly for raw waters. UV254 measurements using single wavelength compensation, linear regression compensation and multiplicative scatter correction techniques with the assistant of linear correction methods were confirmed to be comparable to the instrument built-in compensation method. Our results reveal that these particle compensation techniques can make the UV254 technology reliable for online water quality monitoring in water treatment network. This paper demonstrated the advantage of using software compensation method to establish local compensation and calibration models instead of relying on the predetermined global calibrations for online water quality monitoring.

Rapid Nondestructive Detection of Water Content and Granulation in Postharvest "Shatian" Pomelo Using Visible/Near-Infrared Spectroscopy.

Visible/near-infrared (VIS/NIR) spectroscopy is a powerful tool for rapid, nondestructive fruit quality detection. This technology has been widely applied for quality detection of small, thin-peeled fruit, though less so for large, thick-peeled fruit due to a weak spectral signal resulting in a reduction of accuracy. More modeling work should be focused on solving this problem. “Shatian” pomelo is a traditional Chinese large, thick-peeled fruit, and granulation and water loss are two major internal quality factors that influence its storage quality. However, there is no efficient, nondestructive detection method for measuring these factors. Thus, the VIS/NIR spectral signal detection of 120 pomelo samples during storage was performed. Information mining (singular sample elimination, data processing, feature extraction) and modeling were performed in different ways to construct the optimal method for achieving an accurate detection. Our results showed that the water content of postharvest pomelo was optimally detected using the Savitzky–Golay method (SG) plus the multiplicative scatter correction method (MSC) for data processing, genetic algorithm (GA) for feature extraction, and partial least squares regression (PLSR) for modeling (the coefficient of determination and root mean squared error of the validation set were 0.712 and 0.0488, respectively). Granulation degree was best detected using SG for data processing and PLSR for modeling (the detection accuracy of the validation set was 100%). Additionally, our research showed a weak relationship between the pomelo water content and granulation degree, which provided a reference for the existing debates. Therefore, our results demonstrated that VIS/NIR combined with optimal information mining and modeling methodswas feasible for determining the water content and granulation degree of postharvest pomelo, and for providing references for the nondestructive internal quality detection of other large, thick-peeled fruits.

Simultaneous scatter rejection and correction method using 2D antiscatter grids for CBCT.

While two-dimensional antiscatter grids (2D grid) reduce scatter intensity substantially in Cone Beam Computed Tomography (CBCT), a small fraction of scattered radiation is transmitted through the 2D grid to the detector. Residual scatter limits the accuracy of CT numbers and interferes with the correction of grid's septal shadows, or footprint, in projections. If grid's septal shadows are not adequately suppressed in projections, it will lead to ring artifacts in CBCT images. In this work, we present a new method to correct residual scatter transmitted through the grid by employing the 2D grid itself as a residual scatter measurement device. Our method, referred as grid-based scatter sampling (GSS), exploits the spatial modulation of primary x-ray fluence by 2D grid's septal shadows. The shape of the signal modulation pattern varies as a function of residual scatter intensity registered by detector pixels. Such a variation in signal pattern was employed to measure residual scatter intensity in each projection, and subsequently, residual scatter was subtracted from each projection. To validate the GSS method, CBCT imaging experiments were conducted using a 2D antiscatter grid prototype in a linac mounted CBCT system. The effect of GSS method on the ring artifact reduction was quantified by measuring noise in CBCT images. In addition, the nonuniformity of Hounsfield Units (HU) and HU accuracy was measured in both head and pelvis-sized phantoms. In qualitative evaluations, GSS method successfully reduced ring artifacts caused by 2D grid's footprint. Image noise reduced by 23% due to reduction of ring artifacts. HU nonuniformity in water-equivalent sections was reduced from 20 HU to 10 HU, and streak artifacts between high density inserts were reduced. The phantom size dependent variations in HU was also reduced after application of GSS method. Without GSS method, HU of density inserts reduced by 9% on the average when phantom size was increased from head to pelvis. With GSS method, HU values reduced only by 5% under the same conditions. In summary, GSS method complements the 2D grid's scatter suppression performance, by correcting the scatter transmitted through the grid. This approach does not require additional scatter-measurement hardware, such as beam-stop arrays, since the grid itself is employed as the scatter measurement device. By suppressing residual scatter in projections, our proposed method successfully reduced artifacts caused by 2D grid's footprint, and further improved CT number accuracy.

Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging—Current Status With Emerging Applications

In this review, we will summarize the past and current state-of-the-art developments in attenuation and scatter correction approaches for hybrid positron emission tomography (PET) and magnetic resonance (MR) imaging. The current status of the methodological advances for producing accurate attenuation and scatter corrections on positron emission tomography/magnetic resonance (PET/MR) systems are described, in addition to emerging clinical and research applications. Future prospects and potential applications which benefit from accurate data corrections to improve the quantitative accuracy and clinical applicability of PET/MR are also discussed. Novel clinical and research applications where improved attenuation and scatter correction methods are beneficial are highlighted.

Scatter Correction for Spectral CT Using a Primary Modulator Mask.

The problem of scattered radiation correction in computed tomography (CT) is well known because scatter induces a bias, a loss of contrast and artifacts. Numerous strategies have been proposed in conventional CT (using energy-integrating detectors) but the problem is still open in the field of spectral CT, a new imaging technique based on energy-selective photon counting detectors. The aim of the present study is to introduce a scatter correction method adapted to multi-energy imaging and based on the use of a primary modulator mask. The main contributions are a correction matrix, which compensates for the effect of the mask, a scatter model based on B-splines and a cost function based on the mask structures and robust to the object structures. The performances of the method have been evaluated on both simulated and experimental data. The mean relative error was reduced from 20% in the lower energy-bins without correction to 4% with the proposed technique, which is close to the error caused by statistical noise.

Technical Note: Long-term stability of Hounsfield unit calibration for cone beam computed tomography.

The goal of this study was to investigate the stability of a phantom-based Hounsfield unit (HU) calibration for cone beam CT (CBCT). Three consecutive scans of a large phantom configuration and a small phantom configuration were acquired and reconstructed with a uniform scatter correction method. The CBCT gray values of the phantom inserts were measured and the three values of each insert averaged. The linear calibration curve was determined and its slope and intercept were evaluated. This procedure was performed for three CBCT scanners (Elekta Synergy) over a period of 10 months with 1, 2, or 4 weeks between measurements. A dosimetric estimation of the HU fluctuations was carried out. The CBCT HUs were stable over time with only small variations in slope and intercept resulting in HU differences on the water level, that is, intercepts, of less than 7HU (standard deviation). Therefore, the dosimetric influence of these HU differences was limited. The inter-scanner disparities (up to~16HU) were larger than the intra-scanner ones (up to~7HU). Stable HUs were observed over a period of 10 months. Due to the differences between the CBCT scanners, scanner-specific calibration curves are necessary.

Investigating aquaphotomics for temperature-independent prediction of soluble solids content of pure apple juice

The methods of aquaphotomics were explored as an aid to improve near infrared spectroscopic predictive modelling of the soluble solids content of pure apple juice at different temperatures. The study focussed on the first overtone region of the O–H stretching vibration of water (1300–1600 nm). A transmission-based FT-NIR (Fourier transform near infrared) spectrometer was used to acquire 103 spectra of freshly expressed juice samples from individual ‘Braeburn’ apples over the wavelength range of 870–1800 nm with a 1 mm cuvette at three temperatures, 20, 25 and 30°C. The aquagram of the first overtone water region showed a trend of increasing bound water absorption with rising soluble solids content, from 7.3 to 13.7°Brix, and increasing free water absorption with rising temperature from 20 to 30°C. Predictive models for apple juice soluble solids content at 25°C were developed using partial least squares regression with spectral pre-processing by standard normal variate (SNV) followed by second derivative transformation (SNV + 2D) or no pre-processing on absorbance spectra at all. The best result, with lowest standard error of prediction of 0.38°Brix, was obtained using the first overtone water region with partial least squares regression on the SNV + 2D spectra. The method of extended multiplicative scatter correction was used, as an additional pre-processing step, to improve apple juice soluble solids content prediction at different temperatures. The interference component selected for the extended multiplicative scatter correction method was the first principal component loading measured using pure water samples taken at the same three temperatures (20, 25 and 30°C). Such extended multiplicative scatter correction pre-processing greatly reduced the soluble solids content prediction bias, when applying the partial least squares regression model developed at 20°C to samples measured at 25 and 30°C, from 0.23 to 0.08 and 0.36 to 0.13°Brix, respectively. Model precision (in terms of standard error of prediction) was also slightly improved by 0.02°Brix in each case, from 0.40 to 0.38 and 0.46 to 0.44°Brix at 25 and 30°C respectively.

Optimization of Scatter Correction Method in Samarium-153 Single-photon Emission Computed Tomography using Triple-Energy Window: A Monte Carlo Simulation Study.

Purpose:In single-photon emission computed tomography imaging, the presence of scatter degrades image quality. The goal of this study is to optimize the main- and sub-energy windows for triple-energy window (TEW) method using Monte Carlo SImulating Medical Imaging Nuclear Detectors (SIMIND) code for samarium-153 (Sm-153) imaging.Materials and Methods:The comparison is based on the Monte Carlo simulation data with the results estimated using TEW method. Siemens Symbia gamma-camera equipped with low-energy high-resolution collimator was simulated for Sm-153 point source located in seven positions in water cylindrical phantom. Three different main-energy window widths (10%, 15%, and 20%) and three different sub-energy window widths (2, 4, and 6 keV) were evaluated. We compared the true scatter fraction determined by SIMIND and scatter fraction estimated using TEW scatter correction method at each position. In order to evaluate the image quality, we used the full width at half maximum (FWHM) computed on the PSF and image contrast using Jaszczak phantom.Results:The scatter fraction using TEW method is similar to the true scatter fraction for 20% of the main-energy window and 6 keV sub-energy windows. For these windows, the results show that the resolution and contrast were improved.Conclusion:TEW method could be a useful scatter correction method to remove the scatter event in the image for Sm-153 imaging.

Assessment of Four Scatter Correction Methods in In-111 SPECT Imaging: A Simulation Study.

Introduction:Detection of compton scattered photons is one of the most important factors affecting the quality of single-photon emission computed tomography (SPECT) images. In most cases, the multiple-energy window acquisition methods are used for estimation of the scatter contribution into the main energy window(s) used in imaging.Aims and Objectives:The purpose of this study is to evaluate and compare the performance of four different scatter correction methods in In-111 SPECT imaging. Due to the lack of sufficient studies in this field, it can be useful to perform a more detailed and comparative study.Materials and Methods:Four approximations for scatter correction of In-111 SPECT images are evaluated by using the Monte Carlo simulation. These methods are firstly applied on each of photopeak windows, separately. Then, the effect of the correction methods is investigated by considering both the photopeak windows. The images obtained from a simulated multiple-spheres phantom are used for the evaluation of the correction methods by using three assessment criteria, including the image contrast, relative noise, and the recovery coefficient.Results:The results of this study show that the correction methods, when using the single photopeak windows, result in increase in image contrast with a significant level of noise. In return, when both the photopeak energy windows are used for imaging, it is possible to achieve the better image characteristics.Conclusion:The use of the proposed correction methods, by considering both the photopeak windows, leads to improve the image contrast with a reasonable level of image noise.