968 resultados para Computed tomography, image quality, dose reduction, iterative reconstruction, model observer
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BACKGROUND: Laparoscopic enucleation for neuroendocrine pancreatic tumors has become a feasible technique, with a reported incidence of pancreatic fistula ranging from 13 to 29 %.1 (-) 3 This report describes the first successful case of laparoscopic pancreatic enucleation with resection of the main pancreatic duct followed by end-to-end anastomosis. METHODS: A 41-year-old woman was admitted to the authors' hospital for repeated syncope. Hypoglycemia also was noted. A contrast-enhanced computed tomography examination showed a highly enhanced tumor measuring 22 mm in diameter on the ventral side of the pancreatic body adjacent to the main pancreatic duct. The patient's blood insulin level was elevated, and her diagnosis was determined to be pancreatic insulinoma. Laparoscopic pancreatic enucleation was performed. Approximately 2 cm of the main pancreatic duct was segmentally resected, and a short stent (Silicone tube: Silastic, Dow Corning Corporation, Midland, MI) was inserted. The direct anastomosis of the main pancreatic duct was performed using four separate sutures with an absorbable monofilament (6-0 PDS). RESULTS: The operation time was 166 min, and the estimated blood loss was 100 mL. The postoperative course was uneventful, and the patient was discharged from hospital on postoperative day 7. The pathologic findings showed a well-differentiated insulinoma and a negative surgical margin. A computed tomography examination performed 1 month after the operation showed a successful anastomosis with a patent main pancreatic duct. CONCLUSIONS: Laparoscopic segmental resection of the main pancreatic duct and end-to-end anastomosis can be performed safely with the insertion of a short stent. This technique also can be used for a central pancreatectomy.
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PURPOSE: To evaluate the technical quality and the diagnostic performance of a protocol with use of low volumes of contrast medium (25 mL) at 64-detector spiral computed tomography (CT) in the diagnosis and management of adult, nontraumatic subarachnoid hemorrhage (SAH). MATERIALS AND METHODS: This study was performed outside the United States and was approved by the institutional review board. Intracranial CT angiography was performed in 73 consecutive patients with nontraumatic SAH diagnosed at nonenhanced CT. Image quality was evaluated by two observers using two criteria: degree of arterial enhancement and venous contamination. The two independent readers evaluated diagnostic performance (lesion detection and correct therapeutic decision-making process) by using rotational angiographic findings as the standard of reference. Sensitivity, specificity, and positive and negative predictive values were calculated for patients who underwent CT angiography and three-dimensional rotational angiography. The intraclass correlation coefficient was calculated to assess interobserver concordance concerning aneurysm measurements and therapeutic management. RESULTS: All aneurysms were detected, either ruptured or unruptured. Arterial opacification was excellent in 62 cases (85%), and venous contamination was absent or minor in 61 cases (84%). In 95% of cases, CT angiographic findings allowed optimal therapeutic management. The intraclass correlation coefficient ranged between 0.93 and 0.95, indicating excellent interobserver agreement. CONCLUSION: With only 25 mL of iodinated contrast medium focused on the arterial phase, 64-detector CT angiography allowed satisfactory diagnostic and therapeutic management of nontraumatic SAH.
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The present study was carried out to check whether classic osteometric parameters can be determined from the 3D reconstructions of MSCT (multislice computed tomography) scans acquired in the context of the Virtopsy project. To this end, four isolated and macerated skulls were examined by six examiners. First the skulls were conventionally (manually) measured using 32 internationally accepted linear measurements. Then the skulls were scanned by the use of MSCT with slice thicknesses of 1.25 mm and 0.63 mm, and the 33 measurements were virtually determined on the digital 3D reconstructions of the skulls. The results of the traditional and the digital measurements were compared for each examiner to figure out variations. Furthermore, several parameters were measured on the cranium and postcranium during an autopsy and compared to the values that had been measured on a 3D reconstruction from a previously acquired postmortem MSCT scan. The results indicate that equivalent osteometric values can be obtained from digital 3D reconstructions from MSCT scans using a slice thickness of 1.25 mm, and from conventional manual examinations. The measurements taken from a corpse during an autopsy could also be validated with the methods used for the digital 3D reconstructions in the context of the Virtopsy project. Future aims are the assessment and biostatistical evaluation in respect to sex, age and stature of all data sets stored in the Virtopsy project so far, as well as of future data sets. Furthermore, a definition of new parameters, only measurable with the aid of MSCT data would be conceivable.
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PURPOSE: To assess the technical feasibility of multi-detector row computed tomographic (CT) angiography in the assessment of peripheral arterial bypass grafts and to evaluate its accuracy and reliability in the detection of graft-related complications, including graft stenosis, aneurysmal changes, and arteriovenous fistulas. MATERIALS AND METHODS: Four-channel multi-detector row CT angiography was performed in 65 consecutive patients with 85 peripheral arterial bypass grafts. Each bypass graft was divided into three segments (proximal anastomosis, course of the graft body, and distal anastomosis), resulting in 255 segments. Two readers evaluated all CT angiograms with regard to image quality and the presence of bypass graft-related abnormalities, including graft stenosis, aneurysmal changes, and arteriovenous fistulas. The results were compared with McNemar test with Bonferroni correction. CT attenuation values were recorded at five different locations from the inflow artery to the outflow artery of the bypass graft. These findings were compared with the findings at duplex ultrasonography (US) in 65 patients and the findings at conventional digital subtraction angiography (DSA) in 27. RESULTS: Image quality was rated as good or excellent in 250 (98%) and in 252 (99%) of 255 bypass segments, respectively. There was excellent agreement both between readers and between CT angiography and duplex US in the detection of graft stenosis, aneurysmal changes, and arteriovenous fistulas (kappa = 0.86-0.99). CT angiography and duplex US were compared with conventional DSA, and there was no statistically significant difference (P >.25) in sensitivity or specificity between CT angiography and duplex US for both readers for detection of hemodynamically significant bypass stenosis or occlusion, aneurysmal changes, or arteriovenous fistulas. Mean CT attenuation values ranged from 232 HU in the inflow artery to 281 HU in the outflow artery of the bypass graft. CONCLUSION: Multi-detector row CT angiography may be an accurate and reliable technique after duplex US in the assessment of peripheral arterial bypass grafts and detection of graft-related complications, including stenosis, aneurysmal changes, and arteriovenous fistulas.
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This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.
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Breathing-induced bulk motion of the myocardium during data acquisition may cause severe image artifacts in coronary magnetic resonance angiography (MRA). Current motion compensation strategies include breath-holding or free-breathing MR navigator gating and tracking techniques. Navigator-based techniques have been further refined by the applications of sophisticated 2D k-space reordering techniques. A further improvement in image quality and a reduction of relative scanning duration may be expected from a 3D k-space reordering scheme. Therefore, a 3D k-space reordered acquisition scheme including a 3D navigator gated and corrected segmented k-space gradient echo imaging sequence for coronary MRA was implemented. This new zonal motion-adapted acquisition and reordering technique (ZMART) was developed on the basis of a numerical simulation of the Bloch equations. The technique was implemented on a commercial 1.5T MR system, and first phantom and in vivo experiments were performed. Consistent with the results of the theoretical findings, the results obtained in the phantom studies demonstrate a significant reduction of motion artifacts when compared to conventional (non-k-space reordered) gating techniques. Preliminary in vivo findings also compare favorably with the phantom experiments and theoretical considerations. Magn Reson Med 45:645-652, 2001.
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Multispectral images contain information from several spectral wavelengths and currently multispectral images are widely used in remote sensing and they are becoming more common in the field of computer vision and in industrial applications. Typically, one multispectral image in remote sensing may occupy hundreds of megabytes of disk space and several this kind of images may be received from a single measurement. This study considers the compression of multispectral images. The lossy compression is based on the wavelet transform and we compare the suitability of different waveletfilters for the compression. A method for selecting a wavelet filter for the compression and reconstruction of multispectral images is developed. The performance of the multidimensional wavelet transform based compression is compared to other compression methods like PCA, ICA, SPIHT, and DCT/JPEG. The quality of the compression and reconstruction is measured by quantitative measures like signal-to-noise ratio. In addition, we have developed a qualitative measure, which combines the information from the spatial and spectral dimensions of a multispectral image and which also accounts for the visual quality of the bands from the multispectral images.
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For decades, lung cancer has been the most common cancer in terms of both incidence and mortality. There has been very little improvement in the prognosis of lung cancer. Early treatment following early diagnosis is considered to have potential for development. The National Lung Screening Trial (NLST), a large, well-designed randomized controlled trial, evaluated low-dose computed tomography (LDCT) as a screening tool for lung cancer. Compared with chest X-ray, annual LDCT screening reduced death from lung cancer and overall mortality by 20 and 6.7 %, respectively, in high-risk people aged 55-74 years. Several smaller trials of LDCT screening are under way, but none are sufficiently powered to detect a 20 % reduction in lung cancer death. Thus, it is very unlikely that the NLST results will be replicated. In addition, the NLST raises several issues related to screening, such as the high false-positive rate, overdiagnosis and cost. Healthcare providers and systems are now left with the question of whether the available findings should be translated into practice. We present the main reasons for implementing lung cancer screening in high-risk adults and discuss the main issues related to lung cancer screening. We stress the importance of eligibility criteria, smoking cessation programs, primary care physicians, and informed-decision making should lung cancer screening be implemented. Seven years ago, we were waiting for the results of trials. Such evidence is now available. Similar to almost all other cancer screens, uncertainties exist and persist even after recent scientific efforts and data. We believe that by staying within the characteristics of the original trial and appropriately sharing the evidence as well as the uncertainties, it is reasonable to implement a LDCT lung cancer screening program for smokers and former smokers.
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Abstract Objective: To propose a protocol for pulmonary angiography using 64-slice multidetector computed tomography (64-MDCT) with 50 mL of iodinated contrast material, in an unselected patient population, as well as to evaluate vascular enhancement and image quality. Materials and Methods: We evaluated 29 patients (22-86 years of age). The body mass index ranged from 19.0 kg/m2 to 41.8 kg/m2. Patients underwent pulmonary CT angiography in a 64-MDCT scanner, receiving 50 mL of iodinated contrast material via venous access at a rate of 4.5 mL/s. Bolus tracking was applied in the superior vena cava. Two experienced radiologists assessed image quality and vascular enhancement. Results: The mean density was 382 Hounsfield units (HU) for the pulmonary trunk; 379 and 377 HU for the right and left main pulmonary arteries, respectively; and 346 and 364 HU for the right and left inferior pulmonary arteries, respectively. In all patients, subsegmental arteries were analyzed. There were streak artifacts from contrast material in the superior vena cava in all patients. However, those artifacts did not impair the image analysis. Conclusion: Our findings suggest that pulmonary angiography using 64-MDCT with 50 mL of iodinated contrast can produce high quality images in unselected patient populations.
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Abstract Objective: To evaluate three-dimensional translational setup errors and residual errors in image-guided radiosurgery, comparing frameless and frame-based techniques, using an anthropomorphic phantom. Materials and Methods: We initially used specific phantoms for the calibration and quality control of the image-guided system. For the hidden target test, we used an Alderson Radiation Therapy (ART)-210 anthropomorphic head phantom, into which we inserted four 5mm metal balls to simulate target treatment volumes. Computed tomography images were the taken with the head phantom properly positioned for frameless and frame-based radiosurgery. Results: For the frameless technique, the mean error magnitude was 0.22 ± 0.04 mm for setup errors and 0.14 ± 0.02 mm for residual errors, the combined uncertainty being 0.28 mm and 0.16 mm, respectively. For the frame-based technique, the mean error magnitude was 0.73 ± 0.14 mm for setup errors and 0.31 ± 0.04 mm for residual errors, the combined uncertainty being 1.15 mm and 0.63 mm, respectively. Conclusion: The mean values, standard deviations, and combined uncertainties showed no evidence of a significant differences between the two techniques when the head phantom ART-210 was used.
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This thesis deals with distance transforms which are a fundamental issue in image processing and computer vision. In this thesis, two new distance transforms for gray level images are presented. As a new application for distance transforms, they are applied to gray level image compression. The new distance transforms are both new extensions of the well known distance transform algorithm developed by Rosenfeld, Pfaltz and Lay. With some modification their algorithm which calculates a distance transform on binary images with a chosen kernel has been made to calculate a chessboard like distance transform with integer numbers (DTOCS) and a real value distance transform (EDTOCS) on gray level images. Both distance transforms, the DTOCS and EDTOCS, require only two passes over the graylevel image and are extremely simple to implement. Only two image buffers are needed: The original gray level image and the binary image which defines the region(s) of calculation. No other image buffers are needed even if more than one iteration round is performed. For large neighborhoods and complicated images the two pass distance algorithm has to be applied to the image more than once, typically 3 10 times. Different types of kernels can be adopted. It is important to notice that no other existing transform calculates the same kind of distance map as the DTOCS. All the other gray weighted distance function, GRAYMAT etc. algorithms find the minimum path joining two points by the smallest sum of gray levels or weighting the distance values directly by the gray levels in some manner. The DTOCS does not weight them that way. The DTOCS gives a weighted version of the chessboard distance map. The weights are not constant, but gray value differences of the original image. The difference between the DTOCS map and other distance transforms for gray level images is shown. The difference between the DTOCS and EDTOCS is that the EDTOCS calculates these gray level differences in a different way. It propagates local Euclidean distances inside a kernel. Analytical derivations of some results concerning the DTOCS and the EDTOCS are presented. Commonly distance transforms are used for feature extraction in pattern recognition and learning. Their use in image compression is very rare. This thesis introduces a new application area for distance transforms. Three new image compression algorithms based on the DTOCS and one based on the EDTOCS are presented. Control points, i.e. points that are considered fundamental for the reconstruction of the image, are selected from the gray level image using the DTOCS and the EDTOCS. The first group of methods select the maximas of the distance image to new control points and the second group of methods compare the DTOCS distance to binary image chessboard distance. The effect of applying threshold masks of different sizes along the threshold boundaries is studied. The time complexity of the compression algorithms is analyzed both analytically and experimentally. It is shown that the time complexity of the algorithms is independent of the number of control points, i.e. the compression ratio. Also a new morphological image decompression scheme is presented, the 8 kernels' method. Several decompressed images are presented. The best results are obtained using the Delaunay triangulation. The obtained image quality equals that of the DCT images with a 4 x 4
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The ongoing development of the digital media has brought a new set of challenges with it. As images containing more than three wavelength bands, often called spectral images, are becoming a more integral part of everyday life, problems in the quality of the RGB reproduction from the spectral images have turned into an important area of research. The notion of image quality is often thought to comprise two distinctive areas – image quality itself and image fidelity, both dealing with similar questions, image quality being the degree of excellence of the image, and image fidelity the measure of the match of the image under study to the original. In this thesis, both image fidelity and image quality are considered, with an emphasis on the influence of color and spectral image features on both. There are very few works dedicated to the quality and fidelity of spectral images. Several novel image fidelity measures were developed in this study, which include kernel similarity measures and 3D-SSIM (structural similarity index). The kernel measures incorporate the polynomial, Gaussian radial basis function (RBF) and sigmoid kernels. The 3D-SSIM is an extension of a traditional gray-scale SSIM measure developed to incorporate spectral data. The novel image quality model presented in this study is based on the assumption that the statistical parameters of the spectra of an image influence the overall appearance. The spectral image quality model comprises three parameters of quality: colorfulness, vividness and naturalness. The quality prediction is done by modeling the preference function expressed in JNDs (just noticeable difference). Both image fidelity measures and the image quality model have proven to be effective in the respective experiments.
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The problem of understanding how humans perceive the quality of a reproduced image is of interest to researchers of many fields related to vision science and engineering: optics and material physics, image processing (compression and transfer), printing and media technology, and psychology. A measure for visual quality cannot be defined without ambiguity because it is ultimately the subjective opinion of an “end-user” observing the product. The purpose of this thesis is to devise computational methods to estimate the overall visual quality of prints, i.e. a numerical value that combines all the relevant attributes of the perceived image quality. The problem is limited to consider the perceived quality of printed photographs from the viewpoint of a consumer, and moreover, the study focuses only on digital printing methods, such as inkjet and electrophotography. The main contributions of this thesis are two novel methods to estimate the overall visual quality of prints. In the first method, the quality is computed as a visible difference between the reproduced image and the original digital (reference) image, which is assumed to have an ideal quality. The second method utilises instrumental print quality measures, such as colour densities, measured from printed technical test fields, and connects the instrumental measures to the overall quality via subjective attributes, i.e. attributes that directly contribute to the perceived quality, using a Bayesian network. Both approaches were evaluated and verified with real data, and shown to predict well the subjective evaluation results.
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Coronary artery disease (CAD) is a chronic process that evolves over decades and may culminate in myocardial infarction (MI). While invasive coronary angiography (ICA) is still considered the gold standard of imaging CAD, non-invasive assessment of both the vascular anatomy and myocardial perfusion has become an intriguing alternative. In particular, computed tomography (CT) and positron emission tomography (PET) form an attractive combination for such studies. Increased radiation dose is, however, a concern. Our aim in the current thesis was to test novel CT and PET techniques alone and in hybrid setting in the detection and assessment of CAD in clinical patients. Along with diagnostic accuracy, methods for the reduction of the radiation dose was an important target. The study investigating the coronary arteries of patients with atrial fibrillation (AF) showed that CAD may be an important etiology of AF because a high prevalence of CAD was demonstrated within AF patients. In patients with suspected CAD, we demonstrated that a sequential, prospectively ECG-triggered CT technique was applicable to nearly 9/10 clinical patients and the radiation dose was over 60% lower than with spiral CT. To detect the functional significance of obstructive CAD, a novel software for perfusion quantification, CarimasTM, showed high reproducibility with 15O-labelled water in PET, supporting feasibility and good clinical accuracy. In a larger cohort of 107 patients with moderate 30-70% pre-test probability of CAD, hybrid PET/CT was shown to be a powerful diagnostic method in the assessment of CAD with diagnostic accuracy comparable to that of invasive angiography and fractional flow reserve (FFR) measurements. A hybrid study may be performed with a reasonable radiation dose in a vast majority of the cases, improving the performance of stand-alone PET and CT angiography, particularly when the absolute quantification of the perfusion is employed. These results can be applied into clinical practice and will be useful for daily clinical diagnosis of CAD.
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The single photon emission microscope (SPEM) is an instrument developed to obtain high spatial resolution single photon emission computed tomography (SPECT) images of small structures inside the mouse brain. SPEM consists of two independent imaging devices, which combine a multipinhole collimator, a high-resolution, thallium-doped cesium iodide [CsI(Tl)] columnar scintillator, a demagnifying/intensifier tube, and an electron-multiplying charge-coupling device (CCD). Collimators have 300- and 450-µm diameter pinholes on tungsten slabs, in hexagonal arrays of 19 and 7 holes. Projection data are acquired in a photon-counting strategy, where CCD frames are stored at 50 frames per second, with a radius of rotation of 35 mm and magnification factor of one. The image reconstruction software tool is based on the maximum likelihood algorithm. Our aim was to evaluate the spatial resolution and sensitivity attainable with the seven-pinhole imaging device, together with the linearity for quantification on the tomographic images, and to test the instrument in obtaining tomographic images of different mouse organs. A spatial resolution better than 500 µm and a sensitivity of 21.6 counts·s-1·MBq-1 were reached, as well as a correlation coefficient between activity and intensity better than 0.99, when imaging 99mTc sources. Images of the thyroid, heart, lungs, and bones of mice were registered using 99mTc-labeled radiopharmaceuticals in times appropriate for routine preclinical experimentation of <1 h per projection data set. Detailed experimental protocols and images of the aforementioned organs are shown. We plan to extend the instrument's field of view to fix larger animals and to combine data from both detectors to reduce the acquisition time or applied activity.