Computed tomography (CT) imaging with high energy resolution detectors shows great promise in material decomposition and multi-contrast imaging. Multi-contrast imaging was studied by imaging a phantom with iodine (I),...
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Computed tomography (CT) imaging with high energy resolution detectors shows great promise in material decomposition and multi-contrast imaging. Multi-contrast imaging was studied by imaging a phantom with iodine (I), gadolinium (Gd), and gold (Au) solutions, and mixtures of the three using a cadmium telluride (CdTe) spectrometer with an energy resolution of 1% as well as with a cadmium zinc telluride (CZT) detector with an energy resolution of 13%. The phantom was imaged at 120 kVp and 1.1 mA with 7 mm of aluminum filtration. For the CdTe data collection, the phantom was imaged using a 0.2 mm diameter x-ray beam with 96 ten-second data acquisitions across the phantom at 45 rotation angles. For the CZT detector, we had 720 projections using a cone beam, and the six detector energy thresholds were set to 23, 33, 50, 64, 81, and 120 keV so that three thresholds corresponded to the K-edges of the contrast agents. Contrast agent isolation methods were then examined. K-edge subtraction and novel spectrometric algebraic imagereconstruction (SAIR) were used for the CdTe data. K-edge subtraction alone was used for the CZT data. Linearity plots produced similar R-2 values and slopes for all three reconstructionmethods. Comparing CdTe methods, SAIR offered less noise than CdTe K-edge subtraction and better geometric accuracy at low contrast concentrations. CdTe contrast agent images of I, Gd, and Au offered less noise and greater contrast than the CZT images, highlighting the benefits of high energy resolution CdTe detectors for possible use in pre-clinical or clinical CT imaging.
The purpose of the present work is the study of reconstruction properties of a new Molecular Breast Imaging (MBI) device for the early diagnosis of breast cancer, in Limited Angle Tomography (LAT), by using two asymme...
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The purpose of the present work is the study of reconstruction properties of a new Molecular Breast Imaging (MBI) device for the early diagnosis of breast cancer, in Limited Angle Tomography (LAT), by using two asymmetric detector heads with different collimators. The detectors face each other in anti-parallel viewing direction and, mild-compressing the breast phantom, they are able to reconstruct the inner tumour of the phantoms with only a limited number of projections using a dedicated maximum-likelihood expectation maximization algorithm. The phantoms, the MBI system, as well as the Monte Carlo simulator, are briefly described. The MBI system's model has been implemented in IDL, in order to evaluate the best LAT configuration of the system and its reconstruction ability by varying tumour's size, depth and uptake. The LAT setup in real and simulated configurations, as well as the maximum-likelihood method and the preliminary reconstruction results, are discussed.
作者:
Ozsahin, I.Near East Univ
Fac Engn Dept Biomed Engn Mersin 10 TRNC TR-99138 Nicosia Turkey Near East Univ
DESAM Inst Mersin 10 TRNC TR-99138 Nicosia Turkey
Recent developments in molecular imaging have led to increases in the performance and area of utilization of positron emission tomography (PET) systems. There are several ways that PET system sensitivity can be increa...
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Recent developments in molecular imaging have led to increases in the performance and area of utilization of positron emission tomography (PET) systems. There are several ways that PET system sensitivity can be increased including changing the scanner's geometry. I recently proposed a novel PET design with adjustable field of view (FOV) to improve the system sensitivity up to 40 times higher than the conventional systems, depending on the size of the transaxial FOV. This study aims to evaluate the spatial resolution characteristics of the proposed design. Geant4-based Architecture for Medicine Oriented Simulations (GAMOS) toolkit was used to simulate the system. The proposed PET geometry was designed to cover and scan the full-body of the patient in one bed position. The spatial resolution tests were conducted using a point like source placed at different locations throughout the FOV when the transaxial FOV of the scanner was changed from 70 cm to 30 cm. The results showed that the spatial resolution slightly degrades when the FOV is reduced.
In the last decade, different positron emission tomography (PET) crystals have been proposed for brain PET detectors. Brain PET cameras with restricted field of view to a smaller size to cover the brain can both exhib...
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In the last decade, different positron emission tomography (PET) crystals have been proposed for brain PET detectors. Brain PET cameras with restricted field of view to a smaller size to cover the brain can both exhibit significantly higher performance and lower the cost when compared to conventional whole-body PET scanners. The existing designs based on scintillation crystals employ the most commonly known materials such as lutetium oxyorthosilicate and bismuth germanate. This is due to their relatively good parameters such as high light yield and density. The main drawback of using scintillation crystals is that they have a modest energy resolution. In this study, a brain PET scanner was designed and simulated using a Geant4 Application for Tomographic Emission (GATE) toolkit. The performances of five crystals, namely strontium hafnate, gadolinium aluminium gallium garnet, gadolinium yttrium gallium aluminium garnet, gadolinium lutetium gallium aluminium garnet, and lutetium oxyorthosilicate for comparison, were evaluated in terms of sensitivity, spatial resolution, and count rate. The performance evaluation results showed that among the suggested scintillators, strontium hafnate can be considered as a promising alternative detector for high performance brain PET systems.
Using coded aperture, for localization of radioactive hot-spots, results in enhanced efficiency and under certain configurations wide Field of View (FOV). We present a coded aperture assembly technique which can be re...
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Using coded aperture, for localization of radioactive hot-spots, results in enhanced efficiency and under certain configurations wide Field of View (FOV). We present a coded aperture assembly technique which can be restructured easily, as well as the reduction of the intrinsic noise of coded apertures constructed with this technique, when they localize spatially extended gamma-emitters. Specifically, Modified-Uniformly-Redundant-Array (MURA) coded apertures are structured by embedding lead spheres in a matrix of positions machined inside a transparent medium such as acrylic glass, resulting in an advantageous transparent to opaque area ratio and thus an improved detection efficiency. This configuration also induces a systematic, element-wise, noise on the Point-Spread-Function (PSF) of the correlation matrix. When imaging with these apertures extended hot-spots, a penumbra phenomenon occurrs and reduces this intrinsic noise, in the way a kernel filter does. Fast-Fourier-Transform (FFT) is used to analyze the effect of this phenomenon on the correlation matrix and to explain the maximization of its Signal-to-Noise Ratio (SNR) for certain extent of the hot-spots. Simulations have been used for the detailed study of the SNR dependence on the dimensions of the hot-spot, while experiments with two Tc-99m cylindrical sources with 11mm and 24mm diameter, respectively and 1.5MBq activity each, confirm the reduction of the intrinsic noise. The results define the way of optimization of the imaging setup for the detection of extended hot-spots. Such an optimization could be useful for example in the case of lymph nodes or thyroid remnant imaging in nuclear medicine. Finally, we propose a kernel filter, derived by the Auto-Correlation-Function (ACF), to be applied on PSFs with high intrinsic noise, in order to eliminate it.
Artificial intelligence plays an important role in the classification of medicalimages for computerized diagnosis of the disease. The computer-aidedmedical imaging analysis system is developed for breast tissue dens...
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Artificial intelligence plays an important role in the classification of medicalimages for computerized diagnosis of the disease. The computer-aidedmedical imaging analysis system is developed for breast tissue density classification in mammogram images. Mammogram density is considered as significant predictive markers for breast cancer detection, treatment and management. Recently, deep learning techniques achieved impressive results in computer-assisted disease diagnosis. The deep learning technique such as the convolution neural network (CNN) is used for automated classification of mammogram density as fatty, dense and glandular. This study investigates how computer-aidedmedical imaging analysis system provides a reliable classification of mammogram density. The proposed methodology is evaluated using a mini-MIAS (Mammogram image Analysis Society) database. We obtained an average accuracy of 98.5%. So, the proposed CAD system aids the clinicians in the classification of mammogram density.
In the last decade, different positron emission tomography (PET) crystals have been proposed for brain PET detectors. Brain PET cameras with restricted field of view to a smaller size to cover the brain can both exhib...
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In the last decade, different positron emission tomography (PET) crystals have been proposed for brain PET detectors. Brain PET cameras with restricted field of view to a smaller size to cover the brain can both exhibit significantly higher performance and lower the cost when compared to conventional whole-body PET scanners. The existing designs based on scintillation crystals employ the most commonly known materials such as lutetium oxyorthosilicate and bismuth germanate. This is due to their relatively good parameters such as high light yield and density. The main drawback of using scintillation crystals is that they have a modest energy resolution. In this study, a brain PET scanner was designed and simulated using a Geant4 Application for Tomographic Emission (GATE) toolkit. The performances of five crystals, namely strontium hafnate, gadolinium aluminium gallium garnet, gadolinium yttrium gallium aluminium garnet, gadolinium lutetium gallium aluminium garnet, and lutetium oxyorthosilicate for comparison, were evaluated in terms of sensitivity, spatial resolution, and count rate. The performance evaluation results showed that among the suggested scintillators, strontium hafnate can be considered as a promising alternative detector for high performance brain PET systems.
Using coded aperture, for localization of radioactive hot-spots, results in enhanced efficiency and under certain configurations wide Field of View (FOV). We present a coded aperture assembly technique which can be re...
详细信息
Using coded aperture, for localization of radioactive hot-spots, results in enhanced efficiency and under certain configurations wide Field of View (FOV). We present a coded aperture assembly technique which can be restructured easily, as well as the reduction of the intrinsic noise of coded apertures constructed with this technique, when they localize spatially extended gamma-emitters. Specifically, Modified-Uniformly-Redundant-Array (MURA) coded apertures are structured by embedding lead spheres in a matrix of positions machined inside a transparent medium such as acrylic glass, resulting in an advantageous transparent to opaque area ratio and thus an improved detection efficiency. This configuration also induces a systematic, element-wise, noise on the Point-Spread-Function (PSF) of the correlation matrix. When imaging with these apertures extended hot-spots, a penumbra phenomenon occurrs and reduces this intrinsic noise, in the way a kernel filter does. Fast-Fourier-Transform (FFT) is used to analyze the effect of this phenomenon on the correlation matrix and to explain the maximization of its Signal-to-Noise Ratio (SNR) for certain extent of the hot-spots. Simulations have been used for the detailed study of the SNR dependence on the dimensions of the hot-spot, while experiments with two Tc-99m cylindrical sources with 11mm and 24mm diameter, respectively and 1.5MBq activity each, confirm the reduction of the intrinsic noise. The results define the way of optimization of the imaging setup for the detection of extended hot-spots. Such an optimization could be useful for example in the case of lymph nodes or thyroid remnant imaging in nuclear medicine. Finally, we propose a kernel filter, derived by the Auto-Correlation-Function (ACF), to be applied on PSFs with high intrinsic noise, in order to eliminate it.
This study investigated analytic digital tomosynthesis (DTS) reconstruction in partial sampling with a multislit collimator that partially blocks the x-ray beam to the patient during projection data acquisition, there...
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This study investigated analytic digital tomosynthesis (DTS) reconstruction in partial sampling with a multislit collimator that partially blocks the x-ray beam to the patient during projection data acquisition, thereby reducing excessive radiation dose to patients. Partially-sampled DTS images reconstructed using the analytic filtered-backprojection (FBP) algorithm usually suffer from severe bright-band artifacts around multislit edges of the collimator due to incomplete spatial sampling. In this study, a new prior sinogram interpolation method was introduced to the analytic DTS reconstruction in partial sampling to alleviate such artifacts. To verify the proposed DTS method, we conducted a systematic simulation and investigated image characteristics. Three multislit collimator layouts of C(2/2), C(3/3), and C(4/4) with a 50% duty cycle were designed and used in the simulation. Here C(n/n) denotes a collimator layout that blocks the x-ray beam over n detector pixels vertically with a n-pixel interval. All projections were obtained at a tomographic angle of theta = +/- 40 degrees and an angle step of Delta theta = 2 degrees and used to reconstruct DTS images using the FBP algorithm. Our results indicate that the proposed sinogram interpolation method effectively minimized bright-band artifacts in analytic DTS reconstruction in partial sampling, thus maintaining the image quality.
reconstruction algorithm is a key technology for improving the performance of gamma cameras. This paper presents a least squares estimate (LSE) algorithm based on particle swarm optimization (PSO) to estimate the posi...
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reconstruction algorithm is a key technology for improving the performance of gamma cameras. This paper presents a least squares estimate (LSE) algorithm based on particle swarm optimization (PSO) to estimate the position of a scintillation event detected in a continuous crystal by a position sensitive photomultiplier tube (PSPMT). The theoretical framework of this algorithm consists of two parts: an enhanced objective function with a coefficient established by LSE via fitting the charge signals with the Scrimger-Backer formula;PSO method to search the global optimum solution of the objective function. The constant coefficient eta = Q/I introduced to objective function is demonstrated to effectively improve the position linearity response and expand the useful field of view (UFOV) up to almost the dimension of the PSPMT for both wide and narrow light distribution. More powerful global searching ability and highier computational efficiency are shown in PSO-based LSE algorithm in comparison with the gradient-descent-based LSE (GD-based LSE) algorithm. Furthermore, the PSO-based LSE algorithm overcomes the compression effect produced by trunction of light distribution in CoG algorithm and exhibits an almost idea position linearity response as well as 96 similar to 99% ratios of FOV/crystal size for different light distributions.
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