Introduction: Myocardial SPECT imaging is usually performed acquiring 32 views in 180 degree with equal steps of 5.625 degrees. Acquiring more IMAGEs requires spending more time or injection of more activity to the patients. An idea to improve the quality reconstructed IMAGEs without acquiring extra IMAGEs is producing the extra IMAGEs interpolating the data between adjacent projections. The aim of present study was investigation the feasibility of this idea.Methods: Obviously such investigation cannot be performed on real patient's data. Therefore, data were simulated using NCAT digital phantom and SimSET Monte Carlo code. The imaging was performed as usual, acquiring 32 views from right anterior oblique to left posterior oblique. The data were interpolated to construct 5 IMAGEs between adjacent projections convert it into 187 projections. The simulation was performed again acquiring 187 IMAGEs as the reference. The conventional, interpolated and reference data set were reconstructed and compared for improvement and degradation in quality of final IMAGEs. The above procedure was repeated for phantoms representing different types of heart disease, different cardiac size and different count densities.Results: The results showed that Hermit interpolation technique produces better quality IMAGEs comparing to other interpolation methods tested. Results also confirmed that streak artifacts decreases, signal to noise ratio and contrast increased due to increasing the number of samples.Conclusion: These results indicate that the physical properties of reconstructed IMAGEs improve significantly.This directly must improve the lesions delectability of IMAGEs. However the matter is still under investigation.

Introduction: SPECT is reconstructed using iterative techniques incorporating photon attenuation correction based on the X ray transmission map and scatter correction. Since the quality of IMAGE in SPECT scans depends on the imaging parameters that are determined experimentally in the field of nuclear medicine, designing a dedicated scanning method for 99mTc/SPECT is need to improve the accuracy of disease diagnostic. Therefore, in this study with the aims of assessment and evaluation the effect of different filters on IMAGE quality, assessment of quality criteria on IMAGE before and after optimization and determine optimum algorithm for reconstruction on liver scanning using 99m Tc for SPECT studies. Material and Method: Filtered Back-projection reconstruction method had been used in liver scanning using 99m Tc/EDDA/HYNIC-TOC for SPECT IMAGE and effect of different filters on SPECT imaging have been evaluated. Results and Conclusion: Based on results, we suggest the Hamming filter to be used for visual analysis of Liver SPECT because of its ability to produce the high-quality IMAGE. Instead, the Butterworth filter is suggested for quantitative analysis because of its ability to balance between IMAGE quality and noise.

Objective(s): Various iterative reconstruction algorithms in nuclear medicine have been introduced in the last three decades. For each new imaging system, it is wise to select appropriate IMAGE reconstruction algorithms and evaluate their performance. In this study, three approaches of IMAGE reconstruction were developed for a novel desktop open-gantry SPECT system, PERSPECT, to assess their performance in terms of the quality of the resultant reconstructed IMAGEs.Methods: In the present work, a proposed IMAGE reconstruction algorithm for the PERSPECT, referred to as quasi-simultaneous multiplicative algebraic reconstruction technique (qSMART), together with two popular IMAGE reconstruction methods, maximum-likelihood expectation-maximization (MLEM) and ordered-subsets EM (OSEM), were implemented and compared. Analytic and Monte Carlo simulations were applied for data acquisition of various phantoms including a micro-Derenzo phantom. All acquired data were reconstructed by the three algorithms using different number of iterations (1-40). A thorough set of figures-of-merit was utilized to quantitatively compare the generated IMAGEs.Results: OSEM depicted reconstructed IMAGEs of higher (or matching) quality in comparison to qSMART. MLEM also reached nearly similar quality as OSEM but at higher number of iterations. The graph of data discrepancy revealed that the ranking of the three approaches in terms of convergence speed is as qSMART, OSEM, and MLEM. Furthermore, bias-versus-noise curves indicated that optimal bias-noise results were achieved using OSEM.Conclusion: The results showed that although qSMART can be applied for IMAGE reconstruction if being halted in the early iterations (up to 5), the best achievable quality of IMAGEs is obtained using the OSEM.

Purpose: The quality of the IMAGE in SPECT scans depends on the imaging parameters which are determined experimentally in the field of nuclear medicine. Designing a dedicated scanning parameter for 177Lu-DOTATATE SPECT IMAGEs is required to optimize reconstruction. Therefore, this study aims to evaluate the effect of different filters on IMAGE quality for bone SPECT scanning using 177Lu-DOTATATE. Materials and Methods: The filtered back-projection reconstruction method was used in neuro-endocrine tumor scanning using 177Lu-DOTATATE. Three hours after injection of 177Lu-DOTATATE, SPECT scans from 177Lu-DOTATATE for 30 patients were acquired using a dual-head EvoExel detector system. Seven parameters were considered, including the contrast/noise ratio, injection activity, uptake duration, acquisition time per injection, frame time, measuring time, and type of filters. Results: In all cases, the application of different filters increased Contrast to Noise Ratio (CNR) (9. 1%, 1. 8%, 10. 9%, 61. 8%, 23. 6%, 29. 1%, and 58. 2% for Wiener, Butterworth, Parzen, Metz, Ramp, Shepp-Logan, and Hamming filters, reSPECTively). The percentage of increase in Signal-to-Noise Ratio (SNR) was 3. 3%, 1. 7%,-24%, 21. 7%, 9. 8%, 11. 9%, and 20. 6%. Conclusion: Based on the quantitative analysis of the results, the application of the Metz filter (power 2) and Hamming filter (with 0. 27, 0. 47, and 0. 67 cut-off frequencies) on SPECT scans of neuro-endocrine tumors is recommended because of their capacity to provide high-quality IMAGEs.

Introduction: In SPECT the collimator is a crucial element of the imaging chain and controls the noise resolution tradeoff of the collected data. The detection of photons in SPECT is seriously affected by collisions of the photons with atoms inside the patient (photon attenuation and scatter), and the inevitable inaccuracy of the collimator used (collimator blurring). The IMAGEs are also severely degraded because of noise, partly due to the Poisson nature of the photon emission. Accordingly, it is very difficult to obtain high quality and quantitative accurate SPECT IMAGEs. The lead x-rays, collimator scatter and partial energy deposition in the detector crystal are the effects that contribute to the 99mTc camera down-scatter in the energy range of 100±10% keV or 72±10%. The current study is an evaluation of the effects of low energy high resolution collimator thickness, commonly used in SPECT, on tomographic spatial resolution.Methods: SIMIND Monte Carlo program was used for simulation of a Siemen’s dual-head variable angle scintillation gamma camera and also a related Low Energy High Resolution (LEHR) collimator. For this study a point source of 99mTc and also an acrylic cylindric Jaszczack phantom, with cold spheres and rods, and a NCAT phantom were used. Quantitative and qualitative studies were performed for obtained acquired projections and also reconstructed IMAGEs.Results: Results for calculated detector parameters, contribution of Compton scattering, photoelectric reactions, and also peak to Compton (P/C) area in the obtained energy SPECTrums from scanning of the sources with 11 collimator thickness, ranged from 0.400 to 0.410 cm, were tabulated. The IMAGE quality analyses by SSIM algorithm and also by eye interpretation were provided.Conclusion: There was a suitable quality and also performance parameters analysis results for the projections and reconstructed IMAGEs prepared with a 0.405 mm LEHR collimator thickness compared to other thicknesses.

Background: Single photon emission computed tomography (SPECT) imaging is widely implemented in nuclear medicine for detecting coronary artery diseases. To increase the accuracy of the diagnosis, it is necessary to improve the quality of the SPECT IMAGEs that can be degraded by noise. The aim of this study was to evaluate the effectiveness of using different filters such as Butterworth, Gaussian, Wiener with kernel sizes 3×3 and 5×5, and Median Modified Wiener Filters (MMWF with kernel sizes 3×3 and 5×5 to improve the quality of myocardial perfusion SPECT IMAGEs with 99mTc-MIBI. Methods: A Siemens Symbia T2 dual head SPECT/CT scanner equipped with a low-energy and high-resolution collimator (LEHR) was used for collecting data for this cross-sectional-applied study. The noise ratio (SNR), peak to noise ratio (PSNR) and contrast to noise ratio (CNR) were the indices used to asses the quality of the myocardial perfusion SPECT IMAGEs of 30 patients after the filters mentioned above have been applied to the IMAGEs. Findings: Wiener filter with kernel size of 5×5 4. 90 ±,0. 69 and 2. 65 ±,0. 57 were found be the highest SNR and CNR indices reSPECTively. However, it had the lowest PSNR in the range of 29. 93 ±,3. 13 (dB). In addition, the highest PSNR values were associated with the Gaussian filter as 50. 09 ±,10. 63 (dB). Conclusion: The results of this study show that the wiener filter of kernel size of 5×5 outperformed the others to improve the quality of myocardial perfusion SPECT IMAGEs used in this study.

Purpose: The study purpose was to determine and compare the Recall and Precision of Bing and Google IMAGE search engines for content based IMAGE retrieval. Methodology: The research used webometrics and comparative methods. Population includes IMAGEs stored in the databases of Bing and Google search engines, and research sample includes 15 selective IMAGEs searched in any of search engines. All the retrieved sources through the IMAGEs by IMAGE content based IMAGE search were gathered, results’ Recall and Precision measures were calculated by relevance formula and their average percentage were obtained. Research hypotheses were tested by U Mann-Whitney test as well. Findings: Findings showed that the Google search engine functionality was higher with recall measure of % 88. 73 than recall rate (%20. 86) for Bing. But Bing search engine had higher precision (% 99. 86) than Google (%94. 80). Results: Hypotheses tests on recall and precision in two search engines’ IMAGE retrieval showed a significant difference for recall in favor of Google, indicating its better functionality than Bing but there was no significant difference between them concerning precision since both showed fair precision however Bing was relatively useful.

In this paper, an alternative approach in operational modal analysis is presented, utilizing IMAGE processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, reSPECTively, and in comparison to the analytical values, they are 0.34% and 1.5%, reSPECTively.

Background: In nuclear medicine, phantoms are mainly used to evaluate the overall performance of the imaging systems, and practically there is no phantom exclusively designed for the evaluation of the software performance. In this study the Hoffman brain phantom was used for quantitative evaluation of reconstruction techniques. The phantom is modified to acquire tomographic and planar IMAGE of the same structure. The planar IMAGE may be used as the reference IMAGE to evaluate the quality of reconstructed slices, using the companion software developed in MATLAB. Materials and Methods: The designed phantom was composed of 4 independent 2D slices that could have been placed juxtapose to the 3D phantom. Each slice was composed of objects of different size and shape (for example: circle, triangle, and rectangle). Each 2D slice was IMAGEd at distances ranging from 0 to 15 cm from the collimator surface. The phantom in 3D configuration was IMAGEd acquiring 128 views of 128×128 matrix size. Reconstruction was performed using different filtering condition and the reconstructed IMAGEs were compared to the corresponding planar IMAGEs. The modulation transfer function, scatter fraction and attenuation map were calculated for each reconstructed IMAGE. Results: Since all the parameters of the acquisition were identical for the 2D and the 3D imaging, it was assumed that the difference in the quality of the IMAGEs has exclusively been due to the reconstruction condition. The planar IMAGEs were assumed to be the most perfect IMAGEs which could be obtained with the system. The comparison of the reconstructed slices with the corresponding planar IMAGEs yielded the optimum reconstruction condition. The results clearly showed that Wiener filter yields superior quality IMAGE among the entire tested filters. The extent of the improvement has been quantified in terms of universal IMAGE quality index. Conclusion: The phantom and the accompanying software were evaluated and found to be quite useful in determining the optimum filtering condition and mathematical evaluation of the scatter and attenuation in tomographic IMAGEs.