Higher Image Noise Research Articles

Robust Nanoparticles Detection From Noisy Background by Fusing Complementary Image Information.

This paper studies the problem of detecting the presence of nanoparticles in noisy transmission electron microscopic (TEM) images and then fitting each nanoparticle with an elliptic shape model. In order to achieve robustness while handling low contrast and high noise in the TEM images, we propose an approach to fuse two kinds of complementary image information, namely, the pixel intensity and the gradient (the first derivative in intensity). Our approach entails two main steps: 1) the first step is to, after necessary pre-processing, employ both intensity-based information and gradient-based information to process the same TEM image and produce two independent sets of results and 2) the subsequent step is to formulate a binary integer programming (BIP) problem for conflict resolution among the two sets of results. Solving the BIP problem determines the final nanoparticle identification. We apply our method to a set of TEM images taken under different microscopic resolutions and noise levels. The empirical results show the merit of the proposed method. It can process a TEM image of 1024×1024 pixels in a few minutes, and the processed outcomes appear rather robust.

Efficient decision based algorithm for the removal of high density salt and pepper noise in images

In this paper, an efficient decision based scheme is proposed for the restoration of grayscale and colour images that are heavily corrupted by salt and pepper noise. The processed pixel is examined for 0 or 255; if found true, then it is considered as noisy pixel else not noisy. If found noisy the four neighbours of the noisy pixels are checked for 0 or 255. If all the four neighbours of the corrupted pixel are noisy, the mean of the four neighbours replaces the corrupted pixel. If any of the four neighbours is a non-noisy pixel, calculate the number of corrupted pixels in the current processing window. If the count is less than three then the noisy pixel is replaced by an unsymmetrical trimmed median. If the current window has more than three noisy pixels, then unsymmetrical trimmed mean replaces the corrupted pixels. If all the pixels of the current processing window are noisy then instead of unsymmetrical trimmed mean, global mean of the image is replaced as output. The uncorrupted pixel is left unchanged. The proposed algorithm is tested on various grayscale and colour images and found that it gives excellent PSNR, high IEF and lowest MSE. Also it consumes average time with excellent edge preservation even at higher noise densities. The quality of the results of proposed algorithm is superior when compared to the various state of the art methods.

Automatic spectral imaging protocol selection and iterative reconstruction in abdominal CT with reduced contrast agent dose: initial experience.

To evaluate the feasibility, image quality, and radiation dose of automatic spectral imaging protocol selection (ASIS) and adaptive statistical iterative reconstruction (ASIR) with reduced contrast agent dose in abdominal multiphase CT. One hundred and sixty patients were randomly divided into two scan protocols (n = 80 each; protocol A, 120 kVp/450 mgI/kg, filtered back projection algorithm (FBP); protocol B, spectral CT imaging with ASIS and 40 to 70keV monochromatic images generated per 300 mgI/kg, ASIR algorithm. Quantitative parameters (image noise and contrast-to-noise ratios [CNRs]) and qualitative visual parameters (image noise, small structures, organ enhancement, and overall image quality) were compared. Monochromatic images at 50keV and 60keV provided similar or lower image noise, but higher contrast and overall image quality as compared with 120-kVp images. Despite the higher image noise, 40-keV images showed similar overall image quality compared to 120-kVp images. Radiation dose did not differ between the two protocols, while contrast agent dose in protocol B was reduced by 33%. Application of ASIR and ASIS to monochromatic imaging from 40 to 60keV allowed contrast agent dose reduction with adequate image quality and without increasing radiation dose compared to 120 kVp with FBP. • Automatic spectral imaging protocol selection provides appropriate scan protocols. • Abdominal CT is feasible using spectral imaging and 300 mgI/kg contrast agent. • 50-keV monochromatic images with 50 % ASIR provide optimal image quality.

Feasibility of virtual nonenhanced images derived from single-source fast kVp-switching dual-energy CT in evaluating gastric tumors

PurposeTo assess the feasibility of virtual nonenhanced (VNE) images derived from single-source fast kVp-switching dual-energy CT, namely material suppressed iodine (MSI) images in evaluating gastric tumors, and to calculate potential radiation dose reductions for a dual-phase gemstone spectral imaging (GSI) abdominal CT compared with a standard triple-phase protocol. Materials and methodsThe institutional review board approved this prospective study; all patients provided written informed consent. 95 patients underwent preoperative enhanced CT that included true nonenhanced (TNE) with conventional 120kVp mode, arterial phase (AP) and venous phase (VP) with GSI mode. MSI images were obtained from enhanced images of AP. Two abdominal radiologists independently evaluated the image quality of TNE and MSI images using a 5-point scale. Interobserver agreement was accessed by kappa value. The sensitivity for lesions on TNE and MSI images were evaluated. The CT number of various regions and image noise was measured on TNE and MSI images. The relative enhancement CT value of lesions, contrast to noise(CNR) of gastric tumors and effective radiation doses for triple-phase and dual-phase protocol were calculated. Differences were tested for statistical significance using Wilcoxon signed rank test and paired t-test. ResultsInterobserver agreement about image quality was excellent(all kappa>0.750). No significant difference in image quality was found between TNE 4.32±0.53 and MSI 4.21±0.51 images (P>0.05). In respect to the sensitivities for gastric tumors, lymph node and liver metastasis, there were no significant differences between TNE and MSI images (all P>0.05). The CT number on TNE and MSI images, respectively, for gastric tumor were 32.79HU±6.45 and 35.02HU±5.01 (P=0.006); lymph nodes, 31.33HU±6.37 and 31.61HU±5.73 (P=0.334); liver metastasis, 37.79HU±8.40 and 39.76HU±8.50 (P=0.041); liver, 56.56HU±7.87 and 58.32HU±8.73 (P=0.057); psoas muscle, 52.30HU±5.63 and 51.80HU±6.86 (P=0.533); aorta, 38.16HU±4.91 and 42.49HU±4.49 (P<0.001). The CT relative enhancement value of gastric tumors, lymph node and liver metastasis had no significant difference between TNE and MSI images (P=0.083, 0.194, 0.156). MSI images had higher image noise than TNE images (P<0.001). The CNR of gastric tumor on MSI images was higher than that on TNE images (P<0.001). The effective dose for triple-phase was 25.1mSv±6.2 and that for dual-phase was 17.7mSv±4.1. The dose saving by removing the TNE was 7.5mSv (30.5%). ConclusionIn patients with gastric tumors, the MSI images derived from single-source fast kVp-switching dual-energy CT can provide comparable image quality to TNE images and reliable diagnostic information; replacing TNE images will lower radiation dose by 30.5%.

SU-F-207-12: Optimal CT Scan Mode and Reconstruction Kernel Selection for Bone Fracture Detection Task Under Both Centered and Off-Centered Conditions

Purpose: Hi-Res(olution) mode was introduced in some state-of-the-art CT systems to reduce aliasing and improve spatial resolution. The Hi-Res data can be reconstructed using either the conventional kernels or HD kernels. Since high spatial resolution is often associated with a tremendous increase in image noise, the introduction of Hi-Res has confounded the scan protocol optimization. This work investigated how to use the task-driven optimization framework to optimize the selection of Hi-Res mode and reconstruction kernel for bone fracture detection tasks. Methods: The dependence of spatial resolution on scan mode, reconstruction kernel and off-center position was quantified via MTF measurements. For certain edge enhancing Hi-Res kernels, accuracy of the measurements was confounded by both high image noise and potential CT number saturations. These challenges were addressed by a combined use of repeated scanning and thick-slice reconstructions. Similarly, the NPS was measured under different conditions from repeated scans. The frequency-dependent detectability analysis was used to combine imaging task, MTF, and NPS to quantify the dependence of the overall imaging performance and optimize scan mode and reconstruction kernel selection. Results: (1) For a conventional kernel, the use of Hi-Res significantly improved the MTF at off-centered position. (2) The combined use of Hi-Res mode and HD kernel improved MTF at both the centered and off-centered positions. (3) The use of HD kernels increased noise magnitude and pushed the NPS to higher frequencies, and a model-observer analysis demonstrated that the optimal kernel and scan mode strongly depends on patient position and the nature of the task. This was confirmed by ex vivo animal (bovine bone) experiment. Conclusion: Optimal use of the Hi-Res mode and its associated HD kernels depends on patient positioning and the imaging task. Optimal decision making for its use can be achieved based on the framework developed in this work. J. P. Cruz Bastida, D. Gomez-Cardona, K. Li: Nothing to disclose. T. P. Szczykutowicz: Equipment support, General Electric Company Research Grant, Siemens AG. G.-H. Chen: Research funded, GE Healthcare; Research funded, Siemens AX.

Dark field transmission electron microscopy as a tool for identifying inorganic nanoparticles in biological matrices.

Dark field transmission electron microscopy has been applied herein to visualize the interactions of inorganic nanomaterials with biological systems. This new application of a known technique addresses a deficiency in status quo visualization techniques. High resolution and low noise images can be acquired to locate and identify crystalline nanoparticles in complex biological matrices. Moreover, through the composition of multiple images taken at different angular beam tilts, it is possible to image a majority of nanoparticles present at a site in dark field mode. This facilitates clarity regarding the internalization of nanomaterials in cellular systems. In addition, comparing dark field images recorded at different angular tilts yields insight into the character of nanoparticle faceting.

Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities.

The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.

Geometrical Verification based on a Laser Triangulation System in Industrial Environment. Effect of the Image Noise in the Measurement Results

The use of laser triangulation systems is widely spread in industrial applications, especially in industrial metrology. These applications are usually affected by external perturbations, in particular, image noise and reflections can be an important error source for these kinds of sensors when high precision is required or when the scanning task is developed in an industrial environment. This research is focused in the improvement of the behavior of a laser triangulation sensor working with high noise images. The aim of the image analysis technique is to avoid or reduce the effect of the background noise on the measurement results (flatness). The analysis technique is tested with images captured in the industrial environment of the measurement system. The results show a proper behavior of the algorithm with high noise component images and the feasibility of the technique for use in the inspection of 100% of the production.

Chest CT using spectral filtration: radiation dose, image quality, and spectrum of clinical utility.

To determine the radiation dose, image quality, and clinical utility of non-enhanced chest CT with spectral filtration. We retrospectively analysed 25 non-contrast chest CT examinations acquired with spectral filtration (tin-filtered Sn100 kVp spectrum) compared to 25 examinations acquired without spectral filtration (120 kV). Radiation metrics were compared. Image noise was measured. Contrast-to-noise-ratio (CNR) and figure-of-merit (FOM) were calculated. Diagnostic confidence for the assessment of various thoracic pathologies was rated by two independent readers. Effective chest diameters were comparable between groups (P = 0.613). In spectral filtration CT, median CTDIvol, DLP, and size-specific dose estimate (SSDE) were reduced (0.46 vs. 4.3 mGy, 16 vs. 141 mGy*cm, and 0.65 vs. 5.9 mGy, all P < 0.001). Spectral filtration CT had higher image noise (21.3 vs. 13.2 HU, P < 0.001) and lower CNR (47.2 vs. 75.3, P < 0.001), but was more dose-efficient (FOM 10,659 vs. 2,231/mSv, P < 0.001). Diagnostic confidence for parenchymal lung disease and osseous pathologies was lower with spectral filtration CT, but no significant difference was found for pleural pathologies, pulmonary nodules, or pneumonia. Non-contrast chest CT using spectral filtration appears to be sufficient for the assessment of a considerable spectrum of thoracic pathologies, while providing superior dose efficiency, allowing for substantial radiation dose reduction. • Spectral filtration enables non-contrast chest CT with very high dose efficiency. • This approach reduces CTDI vol , DLP, and SSDE (effective chest diameter 28 cm). • Lung nodules, pneumonia, and pleural pathologies can be assessed with uncompromised confidence.

Assessment of volumetric noise and resolution performance for linear and nonlinear CT reconstruction methods.

For nonlinear iterative image reconstructions (IR), the computed tomography (CT) noise and resolution properties can depend on the specific imaging conditions, such as lesion contrast and image noise level. Therefore, it is imperative to develop a reliable method to measure the noise and resolution properties under clinically relevant conditions. This study aimed to develop a robust methodology to measure the three-dimensional CT noise and resolution properties under such conditions and to provide guidelines to achieve desirable levels of accuracy and precision. The methodology was developed based on a previously reported CT image quality phantom. In this methodology, CT noise properties are measured in the uniform region of the phantom in terms of a task-based 3D noise-power spectrum (NPStask). The in-plane resolution properties are measured in terms of the task transfer function (TTF) by applying a radial edge technique to the rod inserts in the phantom. The z-direction resolution properties are measured from a supplemental phantom, also in terms of the TTF. To account for the possible nonlinearity of IR, the NPStask is measured with respect to the noise magnitude, and the TTF with respect to noise magnitude and edge contrast. To determine the accuracy and precision of the methodology, images of known noise and resolution properties were simulated. The NPStask and TTF were measured on the simulated images and compared to the truth, with criteria established to achieve NPStask and TTF measurements with <10% error. To demonstrate the utility of this methodology, measurements were performed on a commercial CT system using five dose levels, two slice thicknesses, and three reconstruction algorithms (filtered backprojection, FBP; iterative reconstruction in imaging space, IRIS; and sinogram affirmed iterative reconstruction with strengths of 5, SAFIRE5). To achieve NPStask measurements with <10% error, the number of regions of interest needed to be greater than 65. To achieve TTF measurements with <10% error, the contrast-to-noise ratio of the edge needed to be ≥15, achievable by averaging multiple slices across the same edge. The NPStask measured on a commercial CT system showed IR's reduced noise (IRIS, 30% and SAFIRE5, 55%) and "waxier" texture (peak frequencies: FBP, 0.25 mm(-1); IRIS, 0.23 mm(-1); and SAFIRE5, 0.16 mm(-1)). The TTF measured within the axial plane showed improved in-plane resolution with SAFIRE5 at the TTF 50% frequency, f50 (FBP, 0.36-0.41 mm(-1); SAFIRE5, 0.37-0.46 mm(-1)). The TTF measured along the axial direction showed improved z-direction resolution with thinner slice thickness (f50: 0.6 mm, 0.35-0.79 mm(-1); 1.5 mm, 0.22-0.3 mm(-1)) and with SAFIRE5 (f50: FBP, 0.35-0.52 mm(-1); SAFIRE5, 0.42-0.79 mm(-1)). Both in-plane and z-direction resolution of SAFIRE5 showed strong dependency on contrast, reflecting SAFIRE5's nonlinearity. A methodology was developed to measure three-dimensional CT noise and resolution properties for iterative reconstruction, especially at challenging measurement conditions with low contrast and high image noise. The methodology also demonstrated its utility for evaluating commercial CT systems.

SU‐E‐I‐37: Low‐Dose Real‐Time Region‐Of‐Interest X‐Ray Fluoroscopic Imaging with a GPU‐Accelerated Spatially Different Bilateral Filtering

Purpose:The purpose of our study is to reduce imaging radiation dose while maintaining image quality of region of interest (ROI) in X‐ray fluoroscopy. A low‐dose real‐time ROI fluoroscopic imaging technique which includes graphics‐processing‐unit‐ (GPU‐) accelerated image processing for brightness compensation and noise filtering was developed in this study.Methods:In our ROI fluoroscopic imaging, a copper filter is placed in front of the X‐ray tube. The filter contains a round aperture to reduce radiation dose to outside of the aperture. To equalize the brightness difference between inner and outer ROI regions, brightness compensation was performed by use of a simple weighting method that applies selectively to the inner ROI, the outer ROI, and the boundary zone. A bilateral filtering was applied to the images to reduce relatively high noise in the outer ROI images. To speed up the calculation of our technique for real‐time application, the GPU‐acceleration was applied to the image processing algorithm. We performed a dosimetric measurement using an ion‐chamber dosimeter to evaluate the amount of radiation dose reduction. The reduction of calculation time compared to a CPU‐only computation was also measured, and the assessment of image quality in terms of image noise and spatial resolution was conducted.Results:More than 80% of dose was reduced by use of the ROI filter. The reduction rate depended on the thickness of the filter and the size of ROI aperture. The image noise outside the ROI was remarkably reduced by the bilateral filtering technique. The computation time for processing each frame image was reduced from 3.43 seconds with single CPU to 9.85 milliseconds with GPU‐acceleration.Conclusion:The proposed technique for X‐ray fluoroscopy can substantially reduce imaging radiation dose to the patient while maintaining image quality particularly in the ROI region in real‐time.

Richardson–Lucy Deconvolution as a General Tool for Combining Images with Complementary Strengths

We use Richardson-Lucy (RL) deconvolution to combine multiple images of a simulated object into a single image in the context of modern fluorescence microscopy techniques. RL deconvolution can merge images with very different point-spread functions, such as in multiview light-sheet microscopes,1, 2 while preserving the best resolution information present in each image. We show that RL deconvolution is also easily applied to merge high-resolution, high-noise images with low-resolution, low-noise images, relevant when complementing conventional microscopy with localization microscopy. We also use RL deconvolution to merge images produced by different simulated illumination patterns, relevant to structured illumination microscopy (SIM)3, 4 and image scanning microscopy (ISM). The quality of our ISM reconstructions is at least as good as reconstructions using standard inversion algorithms for ISM data, but our method follows a simpler recipe that requires no mathematical insight. Finally, we apply RL deconvolution to merge a series of ten images with varying signal and resolution levels. This combination is relevant to gated stimulated-emission depletion (STED) microscopy, and shows that merges of high-quality images are possible even in cases for which a non-iterative inversion algorithm is unknown.

Pulmonary lobe segmentation based on ridge surface sampling and shape model fitting

Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable. The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes. The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT. The proposed algorithm is effective for lung lobe segmentation in absence of auxiliary structures such as vessels and airways. The most challenging cases are those with mostly incomplete, absent, or near-absent fissures and in cases with poorly revealed fissures due to high image noise. However, the authors observe good performance even in the majority of these cases.

Segmentation of neonatal brain MR images using patch-driven level sets

The segmentation of neonatal brain MR image into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF), is challenging due to the low spatial resolution, severe partial volume effect, high image noise, and dynamic myelination and maturation processes. Atlas-based methods have been widely used for guiding neonatal brain segmentation. Existing brain atlases were generally constructed by equally averaging all the aligned template images from a population. However, such population-based atlases might not be representative of a testing subject in the regions with high inter-subject variability and thus often lead to a low capability in guiding segmentation in those regions. Recently, patch-based sparse representation techniques have been proposed to effectively select the most relevant elements from a large group of candidates, which can be used to generate a subject-specific representation with rich local anatomical details for guiding the segmentation. Accordingly, in this paper, we propose a novel patch-driven level set method for the segmentation of neonatal brain MR images by taking advantage of sparse representation techniques. Specifically, we first build a subject-specific atlas from a library of aligned, manually segmented images by using sparse representation in a patch-based fashion. Then, the spatial consistency in the probability maps from the subject-specific atlas is further enforced by considering the similarities of a patch with its neighboring patches. Finally, the probability maps are integrated into a coupled level set framework for more accurate segmentation. The proposed method has been extensively evaluated on 20 training subjects using leave-one-out cross validation, and also on 132 additional testing subjects. Our method achieved a high accuracy of 0.919±0.008 for white matter and 0.901±0.005 for gray matter, respectively, measured by Dice ratio for the overlap between the automated and manual segmentations in the cortical region.

In Vitro High-Resolution Flat-Panel Computed Tomographic Arthrography for Artificial Cartilage Defect Detection

The objectives of this study were to analyze the spatial resolution of different reconstruction kernels and acquisition protocols, including a prototypic high-resolution protocol in flat-panel (FP) and multidetector (MD) computed tomography (CT), and to evaluate contrast and artificial cartilage depiction quality of in vitro FPCT and MDCT arthrography. An image-quality cone beam phantom was used to compare resolution and different reconstruction kernels of the standard MDCT (120 and 80 kV) and the standard binned (2 × 2) and prototypic high-resolution unbinned (1 × 1) FPCT protocols (5- and 20-second runs each). With the resulting FPCT kernel best matching the standard MDCT kernel (U90u), artificial joint phantoms with differently sized groups of cartilage defects (2, 1, 0.5, and 0.3 mm in width) were then scanned using intra-articular iodinated contrast at 50 mgI/mL. In these joint phantoms, CT numbers and noise in the iodinated contrast and artificial cartilage tissue were measured and contrast-to-noise ratios (CNR) were calculated. Depiction quality of artificial cartilage defects was qualitatively rated by 2 independent radiologists. A sharp reconstruction kernel for all FPCT protocols suited best for matched resolution to the standard MDCT kernel. High-resolution 20-second 1 × 1 binning FPCT showed comparable resolution with MDCT in the range of 0.4 to 1.6 line pairs (lp) per millimeter with superior resolution in higher frequencies than 1.6 lp per millimeter (P < 0.001). Flat-panel computed tomographic 5-second runs were associated with higher image noise than the 20-second runs were. The CNR differed significantly among the protocols (P < 0.01) and was the highest in the 20-second FPCT, followed by the 5-second FPCT 2 × 2 and MDCT protocols. Interreader agreement for the depiction quality of artificial cartilage defects was substantial and high in the joint phantoms (0.74 and 0.81, respectively; P < 0.001). The best ratings of the artificial cartilage defect depiction quality were seen in the FPCT 20-second, followed by the FPCT 5-second and MDCT acquisitions. The depiction quality of smaller cartilage defects (1.0 and 1.67 lp per millimeter) was rated worst in the MDCT acquisitions. In vitro FPCT arthrography offers superior CNR and artificial cartilage defect depiction quality to MDCT, and spatial resolution for small structures is higher when applying high-resolution acquisition protocols. Flat-panel computed tomography, thus, has the potential to improve workflow, and tailored high-resolution protocols may allow for advanced cartilage evaluation in CT arthrography.

Image quality and radiation dose of 128-slice dual-source CT venography using low kilovoltage combined with high-pitch scanning and automatic tube current modulation

To compare vascular enhancement, image quality, and radiation dose of 128-slice dual-source CT venography (CTV) between an imaging setting of 120 kVp with low pitch, and a setting of 100 kVp combined with high pitch and automatic tube current modulation. A total of 100 patients with suspected deep vein thrombosis and varicose veins were divided into two groups: Group 1 [50 patients, 120 kVp, low pitch (0.6), and fixed 120 mA) and Group 2 (50 patients, 100 kVp, high pitch (3.0), and automatic tube current modulation]. Two radiologists, who were blinded to the image protocol, assessed vascular enhancement and image noise in the inferior vena cava (IVC), femoral vein, and popliteal vein. They also assigned an image quality score independently using a 5-point visual scale. Effective dose was estimated using the dose-length product (DLP). Group demographics, radiation dose, vascular enhancement, image noise, and image quality in the two groups were analyzed. Mean vascular enhancement of the IVC, femoral vein, and popliteal vein was significantly higher in group 2 than in group 1, and images in group 2 had significantly higher image noise. However, there were no significant differences in subjective image quality score of the IVC, femoral vein, and popliteal vein. The mean DLP in group 2 (402.10 ± 94.29 mGy cm) was significantly lower than that in group 1 (973.36 ± 63.20 mGy cm) (P < 0.001). Lower extremity CTV using 100 kVp, high pitch (3.0), and automatic tube current modulation improved vascular enhancement with acceptable image quality and low radiation dose.

Automatic tube current modulation for volume scan in a 320-detector row CT scanner

The x-y plane combined with z-axis automatic tube current modulation (ATCM) technique is one of the most comprehensive approaches to CT dose reduction because the radiation dose is adjusted according to patient attenuation in three dimensions. The 320-detector row CT scanner has the widest scan range (16 cm) within one axial rotation and equips with volume scan ATCM (VS-ATCM) mode. Special attention is needed while utilizing VS-ATCM mode in CT acquisitions especially scanning different anatomical regions, such as neck and shoulder in a single volume. However, the mechanism of VS-ATCM of the 320-detector row CT scanner remains unclear. This study aims to evaluate the performance of VS-ATCM mode in a 320-detector row CT scanner. A phantom set consists of three simple-shaped phantoms was scanned with the VS-ATCM mode. A solid-state detector was inserted into the central position of the phantom set to measure the real-time dose profiles at seven positions within five scan volumes. The effective tube-current time product of each slice was recorded. The standard deviation of the CT numbers measured at each image slice was used as a noise measurement. The performance of helical scan ATCM (HS-ATCM) mode was in comparison of VS-ATCM mode. The results indicated that VS-ATCM mode can provide a less dose CT scanning to a patient but resulted in a higher image noise in comparison with those of HS-ATCM mode. In clinical practice, radiologists or radiological technologists should pay more attention on the volume position when using VS-ATCM mode for patient imaging. Our experience can be a reference to others for implementation of clinical practices.

Attenuation-based Automatic Tube Voltage Selection and Tube Current Modulation for Dose Reduction at Contrast-enhanced Liver CT

To retrospectively determine whether the combined use of automatic tube voltage selection (ATVS) and automatic tube current modulation (ATCM) can effectively reduce radiation dose at contrast material-enhanced liver computed tomography (CT) while maintaining acceptable image quality compared with the use of ATCM alone. This study was approved by an institutional review board, and informed consent was waived. Three hundred fourteen consecutive patients suspected of having liver disease were divided into three groups. In two groups, both ATVS and ATCM were used (group A1, n=97; group A2, n=101) but with different contrast gain settings; in one group, only ATCM with a fixed tube potential of 120 kV (group B, n=116) was used. Weighted volume CT dose index and dose-length product, contrast-to-noise ratios (CNRs), and mean image noise were assessed. Qualitative analysis was performed by two board-certified radiologists and one radiology resident. Statistical analysis was performed by using the one-way analysis of variance test, two-tailed paired t test, Kruskal-Wallis test, and noninferiority test. In groups A1 and A2, a significant dose reduction was obtained compared with that in group B (P<.0001). The mean dose reduction was 20% in group A1 and 31% in group A2. Furthermore, CNRs were significantly higher in groups A1 and A2 than in group B (P<.0001). Despite the higher image noise in groups A1 and A2, the overall image quality was acceptable. Compared with the use of ATCM alone, the combined use of ATVS and ATCM allowed reduction of radiation exposure while maintaining good image quality at contrast-enhanced liver CT.

Noise spatial nonuniformity and the impact of statistical image reconstruction in CT myocardial perfusion imaging

To achieve high temporal resolution in CT myocardial perfusion imaging (MPI), images are often reconstructed using filtered backprojection (FBP) algorithms from data acquired within a short-scan angular range. However, the variation in the central angle from one time frame to the next in gated short scans has been shown to create detrimental partial scan artifacts when performing quantitative MPI measurements. This study has two main purposes. (1) To demonstrate the existence of a distinct detrimental effect in short-scan FBP, i.e., the introduction of a nonuniform spatial image noise distribution; this nonuniformity can lead to unexpectedly high image noise and streaking artifacts, which may affect CT MPI quantification. (2) To demonstrate that statistical image reconstruction (SIR) algorithms can be a potential solution to address the nonuniform spatial noise distribution problem and can also lead to radiation dose reduction in the context of CT MPI. Projection datasets from a numerically simulated perfusion phantom and an in vivo animal myocardial perfusion CT scan were used in this study. In the numerical phantom, multiple realizations of Poisson noise were added to projection data at each time frame to investigate the spatial distribution of noise. Images from all datasets were reconstructed using both FBP and SIR reconstruction algorithms. To quantify the spatial distribution of noise, the mean and standard deviation were measured in several regions of interest (ROIs) and analyzed across time frames. In the in vivo study, two low-dose scans at tube currents of 25 and 50 mA were reconstructed using FBP and SIR. Quantitative perfusion metrics, namely, the normalized upslope (NUS), myocardial blood volume (MBV), and first moment transit time (FMT), were measured for two ROIs and compared to reference values obtained from a high-dose scan performed at 500 mA. Images reconstructed using FBP showed a highly nonuniform spatial distribution of noise. This spatial nonuniformity led to large fluctuations in the temporal direction. In the numerical phantom study, the level of noise was shown to vary by as much as 87% within a given image, and as much as 110% between different time frames for a ROI far from isocenter. The spatially nonuniform noise pattern was shown to correlate with the source trajectory and the object structure. In contrast, images reconstructed using SIR showed a highly uniform spatial distribution of noise, leading to smaller unexpected noise fluctuations in the temporal direction when a short scan angular range was used. In the numerical phantom study, the noise varied by less than 37% within a given image, and by less than 20% between different time frames. Also, the noise standard deviation in SIR images was on average half of that of FBP images. In the in vivo studies, the deviation observed between quantitative perfusion metrics measured from low-dose scans and high-dose scans was mitigated when SIR was used instead of FBP to reconstruct images. (1) Images reconstructed using FBP suffered from nonuniform spatial noise levels. This nonuniformity is another manifestation of the detrimental effects caused by short-scan reconstruction in CT MPI. (2) Images reconstructed using SIR had a much lower and more uniform noise level and thus can be used as a potential solution to address the FBP nonuniformity. (3) Given the improvement in the accuracy of the perfusion metrics when using SIR, it may be desirable to use a statistical reconstruction framework to perform low-dose dynamic CT MPI.

Determination of Infarct Size in Ex Vivo Swine Hearts by Multidetector Computed Tomography Using Gadolinium as Contrast Medium

To demonstrate the feasibility of using multidetector computed tomography with gadolinium contrast (Gd-MDCT) for the quantification of myocardial infarct (MI). MI was induced in male swine (n = 6). One week later, the animals received 0.2-mmol/kg gadopentetate dimeglumine and were sacrificed. On the excised hearts, Gd-MDCT with several tube voltages (80, 120, and 140 kV), late gadolinium enhancement MRI (LGE-MRI), and triphenyl-tetrazolium-chloride staining were then conducted. We used a 2-SD threshold for the CT images and several threshold limits (2, 3, 4, 5, 6 SD, and full width at half-maximum [FWHM]) for the LGE-MRI images to delineate the infarct area. Total infarct volume and infarct fraction of each heart were calculated. MI size measured by MDCT at 140 kV showed good correlation with the reference triphenyl-tetrazolium-chloride value. Applying an 80-kV tube voltage, however, significantly underestimated MI size. In our study, the LGE-MRI method, using the 6-SD threshold, provided the most accurate determination of MI size. LGE-MRI, using the 2- and 3-SD threshold limits, significantly overestimated infarct size. The Gd-MDCT technique has been found suitable for the evaluation of MI in an ex vivo experimental setting. Gd-MDCT has the ability to detect MI even at low kV settings, but accuracy is limited by a high image noise because of reduced photon flux.