جستجوی مقالات مرتبط با کلیدواژه « image quality » در نشریات گروه « پزشکی »

Given that the Single Photon Emission Computed Tomography (SPECT) image quality is defined experimentally, developing a specialized scanning technique for each procedure is necessary to increase the diagnosis accuracy. This study aims to determine the optimal algorithm for liver scan reconstruction using 99mTc/SPECT.

The Filtered Back-Projection (FBP) reconstruction method was used in liver scanning using 99mTc-EDDA/HYNIC-TOC (Tektrotyd) for SPECT images of 30 patients which were acquired with a dual-head EvoExel detector system. Using different types of filters in SPECT imaging, various optimal results can be achieved in the processed images, such as artifact reduction, noise reduction, or signal enhancement and recovery. To evaluate the effect of different filters on image quality, Signal-to-Noise-Ratio (SNR), Contrast-to-Noise-Ratio (CNR), and contrast parameters were calculated.

Applying filters enhanced contrast in the images in most cases as well as CNR and SNR. Metz (power = 2), Shepp-Logan (Cut-off frequency = 0.67) and Metz (power = 2) filters increase the CNR, contrast and SNR in images more than the other filters, respectively. The maximum improvement for CNR, contrast and SNR was from 0.62 to 2.35, 0.99 to 1.31, and 8.48 to 14.70, respectively.

Based on the results, the Hamming filter, due to providing high-quality images for visual analysis of liver SPECT, and the Butterworth filter, due to balancing the image quality and noise for quantitative analysis, are recommended.

This study aimed to compare the image quality and volume dose index of head CT scan between two adaptive statistical iterative reconstructions (ASIR) and the filtered back projection (FBP) algorithms. CT number, noise and signal to noise ratio(SNR) for white matter(WM), gray matter(WM), cerebrospinal fluid(CSF( and skull bone were investigated in brain CT scans of 60 patients. All images were reconstructed by FBP and ASIR 40% algorithms. A water phantom was also used to compare the average CT number; noise, signal-to-noise (SNR), and contrast-to-noise ratio (CNR) between algorithms under different acquisition parameters. Volume computed tomography dose index (CTDIvol) and (dose-length product) DLP were obtained from scanner software. Data were analyzed by T-test and Mann-Whitney statistical test with a significance level of less than 0.05. Image noise of gray matter, CSF and skull bone was significantly lower for ASIR algorithm (P<0.05). The difference in SNR for white matter and gray matter was not significant between the two algorithms but it was higher for CSF and bone for ASIR. In phantom study, Image noise, CTDIvol and DLP in both axial and spiral scan modes were higher for FBP algorithm (P<0.05). In addition, there was no significant difference in SNR and CNR between the two algorithms (P>0.05). ASIR algorithm reduces the dose and image noise in head CT scan compared to the filtered back projection. In addition, using ASIR algorithm the image noise does not increase with lower mA.

The study aimed to elucidate the clinical application significance of prospective ECG-gated dual-source CT in central venous (CV) imaging.

Eighty patients who took CT imaging of CV (CTV) check using dual-source Force CT were enrolled. The control group (helical pitch, 0.8; rotation speed, 0.5 s) and the experimental group (rotation speed, 0.25 s). For both groups, image quality and radiation dose were computed.

Cases in the experimental group required longer scanning durations than those in the contro lgroup. In respect to the experimental group, the image quality scores of the superior vena cava and left and right brachiocephalic veins of the patients sharply increased relative to those in the control group. Individuals in the experimental group also presented better image quality scores in left and right subclavian veins, left and right jugular veins, however, this difference was not statistically significant. Lastly, no increase in the radiation dose was bited with the application of prospective ECG gating.

The clinical use of prospective ECG-gated technology significantly reduced cardiovascular pulsing artifact interference on the central vein, especially the superior vena cava segment, and remarkably improved the image quality without increasing the radiation dose to patients.

Computed tomography (CT) of the brain is associated with radiation exposure to the lens of the eyes. Therefore, it is necessary to optimize scan settings to keep radiation exposure as low as reasonably achievable without compromising diagnostic image information. The aim of this study was to compare the effectiveness of the five practical techniques for lowering eye radiation exposure and their effects on diagnostic image quality in pediatric brain CT.

The following scan protocols were performed: reference scan, 0.06‑mm Pbeq bismuth shield, 30% globally lowering tube current (GLTC), reducing tube voltage (RTV) from 120 to 90 kVp, gantry tilting, and combination of gantry tilting with bismuth shielding. Radiation measurements were performed using thermoluminescence dosimeters. Objective and subjective image quality was evaluated.

All strategies significantly reduced eye dose, and increased the posterior fossa artifact index and the temporal lobe artifact index, relative to the reference scan. GLTC and RTV increased image noise, leading to a decrease signal‑to‑noise ratio and contrast‑to‑noise ratio. Except for bismuth shielding, subjective image quality was relatively the same as the reference scan.

Gantry tilting may be the most effective method for reducing eye radiation exposure in pediatric brain CT. When the scanner does not support gantry tilting, GLTC might be an alternative.

Computed tomography (CT) scan is one of the main tools to diagnose and grade COVID‑19 progression. To avoid the side effects of CT imaging, low‑dose CT imaging is of crucial importance to reduce population absorbed dose. However, this approach introduces considerable noise levels in CT images.

In this light, we set out to simulate four reduced dose levels (60% dose, 40% dose, 20% dose, and 10% dose) of standard CT imaging using Beer– Lambert’s law across 49 patients infected with COVID‑19. Then, three denoising filters, namely Gaussian, bilateral, and median, were applied to the different low‑dose CT images, the quality of which was assessed prior to and after the application of the various filters via calculation of peak signal‑to‑noise ratio, root mean square error (RMSE), structural similarity index measure, and relative CT‑value bias, separately for the lung tissue and whole body.

The quantitative evaluation indicated that 10%‑dose CT images have inferior quality (with RMSE = 322.1 ± 104.0 HU and bias = 11.44% ± 4.49% in the lung) even after the application of the denoising filters. The bilateral filter exhibited superior performance to suppress the noise and recover the underlying signals in low‑dose CT images compared to the other denoising techniques. The bilateral filter led to RMSE and bias of 100.21 ± 16.47 HU and − 0.21% ± 1.20%, respectively, in the lung regions for 20%‑dose CT images compared to the Gaussian filter with RMSE = 103.46 ± 15.70 HU and bias = 1.02% ± 1.68% and median filter with RMSE = 129.60 ± 18.09 HU and bias = −6.15% ± 2.24%.

The 20%‑dose CT imaging followed by the bilateral filtering introduced a reasonable compromise between image quality and patient dose reduction.

 Magnetic resonance imaging (MRI) is highly sensitive to motion, resulting in artifacts and lowering image quality. Laryngeal mask airway (LMA) provides numerous advantages over endotracheal tubes as it reduces laryngospasm, coughing, and the risk of postoperative desaturation.

 We aimed to compare LMA with oral airway for airway management during brain MRI in terms of reducing motion artifacts, which can improve image quality.

 This randomized, controlled, double-blind trial was carried out on 40 pediatrics aged 1 - 18 years, American Society of Anesthesiologists (ASA) physical status І and П undergoing brain MRI. Patients were randomized into two equal groups according to the airway method, the control (Guedel oral airway) group and the LMA group. A compatible anesthesia machine was used to provide O2 and sevoflurane 2% - 4%.

 The mean MRI image quality score was significantly higher in the LMA group than in the control group (26.10 ± 3.97 versus 18.60 ± 5.30, P < 0.001). Mean arterial blood pressure and heart rate were significantly lower in the LMA group than in the control group at all study times except at baseline and immediate post-extubation (P < 0.05). Cough was significantly lower in LMA than in the control group (15% vs. 50%, P = 0.040). Airway complications (sore throat, laryngeal spasm, and bronchospasm), nausea, and vomiting did not have a significantly different between the two groups.

 Compared to Guedel oral airway, using LMA for airway management in pediatrics undergoing MRI scans improved the image quality with less cough and better hemodynamics.

To assess and compare image quality characteristics of x-ray computed tomography (CT) and cone beam (CBCT) imaging systems of the Varian linear accelerator.

The CatPhan®504, was examined on the CT simulator (SOMATOM Definition AS, VA48A) and two CBCTs (TrueBeam™ and Clinac® iX linear accelerators) attached to Varian linear accelerator. Image quality parameters including pixel value stability, spatial linearity, pixel size verification, uniformity, noise, spatial resolution, low contrast resolution, and contrast-to-noise ratio (CNR) were assessed using different scanning protocols.

The mean pixel values of regions of interest were stable for CT, TB, and iX-CBCT imaging. Noise on CT was slightly lower and was seen to decrease with increasing mAs, while CNR increased with CT mAs and two CBCTs. For all schemes, the Modulation Transfer Function (MTF) of the reconstructed image was limited by the pixel size. Low contrast targets for TB-CBCT were visible, with up to 6 and 2 targets for 1% and 0.5% for contrast, respectively. However, up to 4 targets of 1% contrast on iX-CBCT images are visible for the low-contrast objectives. Also, up to 8, 4, and 1 targets of 1%, 0.5%, and 0.3% contrast were visible for the low-contrast targets on CT images.

CT and CBCT image quality parameters have been quantified and compared for clinical protocols in different mAs conditions. Selecting the right protocol will boost contrast, based on image quality criteria. The mAs can be decreased to minimize patient dosage.

This study aimed to create a deep learning (DL)-based denoising model using a residual neural network (Res-Net) trained to reduce noise in ring-type dedicated breast positron emission tomography (dbPET) images acquired in about half the emission time, and to evaluate the feasibility and the effectiveness of the model in terms of its noise reduction performance and preservation of quantitative values compared to conventional post-image filtering techniques.

Low-count (LC) and full-count (FC) PET images with acquisition durations of 3 and 7 minutes, respectively, were reconstructed. A Res-Net was trained to create a noise reduction model using fifteen patients’ data. The inputs to the network were LC images and its outputs were denoised PET (LC + DL) images, which should resemble FC images. To evaluate the LC + DL images, Gaussian and non-local mean (NLM) filters were applied to the LC images (LC + Gaussian and LC + NLM, respectively). To create reference images, a Gaussian filter was applied to the FC images (FC + Gaussian). The usefulness of our denoising model was objectively and visually evaluated using test data set of thirteen patients. The coefficient of variation (CV) of background fibroglandular tissue or fat tissue were measured to evaluate the performance of the noise reduction. The SUVmax and SUVpeak of lesions were also measured. The agreement of the SUV measurements was evaluated by Bland–Altman plots.

The CV of background fibroglandular tissue in the LC + DL images was significantly lower (9.10 2.76) than the CVs in the LC (13.60  3.66) and LC + Gaussian images (11.51  3.56). No significant difference was observed in both SUVmax and SUVpeak of lesions between LC + DL and reference images. For the visual assessment, the smoothness rating for the LC + DL images was significantly better than that for the other images except for the reference images.

Our model reduced the noise in dbPET images acquired in about half the emission time while preserving quantitative values of lesions. This study demonstrates that machine learning is feasible and potentially performs better than conventional post-image filtering in dbPET denoising.

Light and portable handheld X-ray devices are being used more often for diagnosis because they allow radiography procedures to be performed on patients in settings where there may not be stationary X-ray devices, such as islands or mountainous regions. In this study, the performances of handheld X-ray devices (HXD) and stationary X-ray devices (SXD) were compared to determine whether the handheld device could produce diagnostically acceptable image quality outside of hospitals, particularly during a global pandemic.

For performance evaluation, the accuracy of tube voltage, reproducibility of X-ray dose, linearity, leakage dose, and accuracy of focal spot size were obtained. The accuracy of the tube voltage and the reproducibility and linearity of the X-ray dose were measured to reduce the frequency of patient reimaging as a performance evaluation of the devices.

After conducting various experiments, it was found that the percentage average error (PAE) value of the tube voltage was -0.01% for the HXD, and the error of the tube voltage was 0.01% for the SXD, which is lower than the standard 10%. Additionally, when using an HXD according to these standards, medical staff is considered safe from exposure to leakage dose because the leakage dose is 0.26 mSv/year without the use of a partition.

Our results provide evidence that images of appropriate quality can be taken with an HXD, offering comparable diagnostic value. It was concluded that the leakage radiation dose would be safe at 0.26 mSv/year without using a radiation shielding partition.

The present study assessed the quality of images and the presence of marginal gaps on cone-beam computed tomography (CBCT) images of teeth restored with all-ceramic and metal-ceramic crowns and compared the gap sizes observed on CBCT images with those obtained on micro-CT images.

Thirty teeth restored with metal-ceramic and all-ceramic crowns, properly adapted and with gaps of 0.30 and 0.50 mm, were submitted to micro-CT and CBCT scans. Linear measurements corresponding to the marginal gap (MG) and the absolute marginal discrepancy (AMD) were obtained. The objective assessment of the quality of CBCT images was performed using the contrast-to-noise ratio (CNR), and the subjective assessment was defined by the diagnoses made by five examiners regarding the presence or absence of gaps.

The measurements were always higher for CBCT, with a significant difference regarding AMD. No significant difference in image quality was observed using CNR between the crowns tested. Low accuracy and sensitivity values could be observed for both crowns.

Marginal mismatch measures were overestimated in CBCT images. No difference in image quality was observed between the crowns. The correct diagnosis of gaps was considered low, irrespective of crown type and gap size.

 Contrast-enhanced chest computed tomography (CT) is useful for the detection and follow-up of patients with lung cancer. However, reaching balance between diagnostic image quality, radiation dose, and iodixanol dose is a cause of concern.

 To investigate the clinical value of adaptive statistical iterative reconstruction (ASIR) in reducing the iodixanol content and radiation dose during contrast-enhanced chest CT scan for patients diagnosed with lung masses/nodules based on the analysis of image quality.

 This prospective study was conducted on 80 patients diagnosed with nodules or masses, who required contrast-enhanced chest CT scans. The experimental group (n = 40) was subjected to iohexol at a high concentration (350 mgI/L) with a tube voltage of 120 kVp and a filter back projection (FBP) reconstruction algorithm. The comparison group (n = 40) was subject to iodixanol at a lower concentration (270 mgI/L) with a tube voltage of 100 kVp and ASIR (blending ratio, 40%). The radiation dose and total iodixanol content, as well as subjective and objective evaluations of image quality, were analyzed and compared.

 The two groups obtained non-significantly different subjective scores for five structures detected in the lung window and five structures detected in the mediastinal window, as well as the overall image (P > 0.05 for all). Both the two-group images obtained diagnosis-acceptable scores (≥ 3 points) on displays of 10 structures and overall image quality. The mean CT value of vessels (100 kVp vs. 120 kVp: 314.90 ± 23.42 vs. 308.93 ± 21.40; P > 0.05), standard deviation (13.03 ± 0.88 vs. 12.83 ± 0.90; P > 0.05), and contrast-to-noise ratio (20.77 ± 2.20 vs. 20.36 ± 1.94; P > 0.05) were not significantly different between two groups. However, the CT dose index, dose-length product, effective dose, and total iodine dose were reduced by 27.58%, 36.65%, 36.59%, and 22.86% in the 100-kVp group compared to the 120-kVp group.

 The ASIR showed great potential in reducing the radiation dose and iodine contrast dose, while maintaining good image quality and providing strong confidence for the diagnosis of lung cancer.

Micro-SPECT system has recently been introduced on nuclear medicine in the preclinical and research in which NaI (Tl) and Cadmium Telluride (CdTe) are used as the gamma-ray detectors with more generally use of NaI (Tl). The present study aimed to evaluate different thicknesses of the NaI (Tl) and (CdTe) detectors on functional parameters of a micro-SPECT system.

A Micro-SPECT system with CdTe semiconductor detector and a hexagonal parallel hole collimator with a hole diameter of 0.11 mm, high of 24.05 mm, and septal thickness of 0.016 mm was simulated by SIMIND Monte Carlo program. The system performance was assessed by comparing the functional parameters, including system efficiency, sensitivity, energy and spatial resolution with the NaI (Tl) detector. The simulated scans of a 99mTc point source, a digital micro-Jacszack phantom, and a voxelized MOBY mouse phantom with the system were prepared to evaluate image quality.

The functional parameters; sensitivity, efficiency, planar spatial resolution, and image contrast of CdTe detector were determined 1.4, 1.2, 1.7, and 1.8 times higher than those of NaI (Tl), respectively. Moreover, the calculated energy resolution of CdTe and NaI (Tl) detectors was obtained 6.2% and 10.2% at 141 KeV, respectively. In the filtered back projection (FBP) reconstructed images of the micro-Jacszack phantom, minimum detectable size of the cold rods with CdTe and NaI (Tl) detectors were obtained 0.79 mm and 0.95 mm, respectively.

The imaging system with a 5.5 mm thickness CdTe detector provided better image quality and showed considerable efficiency.

The effect of region of interest (ROI) size variation on producing accurate noise levels is not yet studied.  This study aimed to evaluate the influence of ROI sizes on the accuracy of noise measurement in computed tomography (CT) by using images of a computational and American College of Radiology (ACR) phantoms. In this experimental study, two phantoms were used, including computational and ACR phantoms. A computational phantom was developed by using Matlab R215a software (Mathworks Inc., Natick, MA Natick, MA) with a homogeneously +100 Hounsfield Unit (HU) value and an added-Gaussian noise with various levels of 5, 10, 25, 50, 75, and 100 HU. The ACR phantom was scanned with a Philips MX-16 slice CT scanner in different slice thicknesses of 1.5, 3, 5, and 7 mm to obtain noise variation. Noise measurement was conducted at the center of the phantom images and four locations close to the edge of the phantom images using different ROI sizes from 3×3 to 41×41 pixels, with an increased size of 2×2 pixels.  The use of a minimum ROI size of 21×21 pixels shows noise in the range of ±5% ground truth noise. The measured noise increases above the ±5% range if the used ROI is smaller than 21×21 pixels.   A minimum acceptable ROI size is required to maintain the accuracy of noise measurement with a size of 21×21 pixels.

Similar to most imaging procedures, the high quality of images is a key factor in ensuring that mammography delivers its full potential benefits. Radiographers play a central role in the acquisition of high-quality images, as they are responsible for not only breast positioning and compression, but also quality control and patient care.

To identify the challenges and difficulties of radiographers in daily practice and to determine the main components of mammography that require further training and education.

An online survey was conducted to collect data regarding the radiographers’ demographic data, institution profile, image assessment tools, mammography challenges, quality control, and continuing professional development.

A total of 73 radiographers participated in this study, the majority of whom were full-time radiographers with a bachelor’s degree in radiography. Less than half of the participants had been a mammographer for more than five years. The American College of Radiology (ACR) criteria were the most familiar image quality assessment tool (52%). The most frequently used scale to evaluate image quality was posterior breast tissue visualization on both craniocaudal (CC) and mediolateral oblique (MLO) views, followed by the pectoral muscle volume determined on the MLO view. Overall, positioning, artifacts, and compression were the main reasons for repeat mammography. Also, wheelchair-bound patients, overweight patients, and breast compression were the greatest challenges of patient positioning.

This pilot study highlighted the importance of developing in-house training courses for radiographers, which focus on patient positioning, image quality assessment, and patient-centered needs to improve practice standards. However, further studies on a larger sample size are needed to validate the present results.

The objective of this study was to investigate the influence of iterative reconstruction (IR) algorithm on radiation dose and image quality of computed tomography (CT) scans of patients with malignant pancreatic lesions by designing a new protocol.

The pancreas CT was performed on 40 patients (23 males and 17 females) with a 160‑slice CT scan machine. The pancreatic parenchymal phase was performed in two stages: one with a usual dose of radiation and the other one after using a reduced dose of radiation. The images obtained with usual dose were reconstructed with Filtered Back Projection (FBP) method (Protocol A); and the images obtained with the reduced dose were reconstructed with both FBP (Protocol B) and IR method (Protocol C). The quality of images and radiation dose were compared among the three protocols.

Image noise was significantly lower with Protocol C (10.80) than with Protocol A (14.98) and Protocol B (20.60) (P < 0.001). Signal‑to‑noise ratio and contrast‑to‑noise ratio were significantly higher with Protocol C than with Protocol A and Protocol B (P < 0.001). Protocol A and Protocol C were not significantly different in terms of image quality scores. Effective dose was reduced by approximately 48% in Protocol C compared with Protocol A (1.20 ± 0.53 mSv vs. 2.33 ± 0.86 mSv, P < 0.001).

Results of this study showed that applying the IR method compared to the FBP method can improve objective image quality, maintain subjective image quality, and reduce the radiation dose of the patients undergo pancreas CT.

Nowadays, there has been a growing demand for low‑dose computed tomography (LDCT) protocols. CT has a critical role in the management of the diagnosis chain of pulmonary disease, especially in lung cancer screening. There have been introduced several dose reduction methods, however, most of them are time‑consuming, intricate, and vendor‑based strategies that are hardly used in clinics routinely. This study aims to evaluate the image quality and pulmonary nodule detectability of LDCT protocols that are feasible and easy implemented. Image quality was analyzed in a general quality control phantom (Gammex) and then in a manmade lung phantom with nodules‑equivalent objects.

This study was designed in a two steps, in the first step, a feasible low‑dose lung CT protocol was selected with quality assessment of accreditation phantom image. In the second step, the selected low‑dose protocol with an appropriate image quality was performed on a manmade lung phantom in which there were objects equivalent to the pulmonary nodule. Finally, image quality parameters of the phantom at the appropriate scan protocol were compared with the standard protocol.

A reduction of about 17% of kVp and 46% in tube current leads to dose reduction by about 70%. The contrast‑to‑noise ratio in the low‑dose protocol remained almost unchanged. The signal‑to‑noise ratio in the low‑dose protocol decreased by approximately 32%, and the noise level has increased by about 1.5 times. However, this reduction method hardly affected the detectability of nodules in man‑made pulmonary phantom.

Here, we demonstrated that the LDCT scan has an insignificant effect on the perception of lung nodules. In this study, patient dose in lung CT was reduced by modifying of kVp and mAs about approximately 70%. Hence, to step in toward low‑dose strategies in medical imaging clinics, using easy‑implemented and feasible low‑dose strategies may be helpful.

A simple noise reduction algorithm, i.e. a selective mean filter (SMF), had been previously introduced. The aim of this study is to investigate the image qualities filtered by a SMF and its comparison to an adaptive statistical iterative reconstruction (ASIR).
To assess the basic image quality, an American Association of Physicists in Medicine Computed Tomography (AAPM CT) performance phantom was used. The phantom was scanned by 128 Multiple Slices Computed Tomography. The tube current varied from 50 mA to 100, 150, and 200 mA. The images of a phantom were reconstructed by filtered back projection (FBP) followed by SMF and ASIR (20, 40, 60, 80, and 100%). The image quality assessment was in terms of noise level, noise power spectrum (NPS), and modulation transfer function (MTF).
The noise level and NPS of SMF was similar with ASIR 100%. The values of the MTF10 of the ASIR filter at any level and SMF were comparable. The MTF10 values of ASIR 60%, and SMF with 50 mA (low) were 0.76 ± 0.02 and 0.75 ± 0.02 cycle/mm, respectively. Meanwhile, the MTF10 of ASIR 60% and SMF with 200 mA (high) were 0.74 ± 0.00 and 0.73 ± 0.00 cycles/mm, respectively.
Our results indicated that the performance of the SMF in reducing noise is equivalent to the maximum level of ASIR strength, i.e., ASIR 100%.