993 resultados para Chest X-ray Images


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An X-ray visualization technique has been used for the quantitative determination of local liquid holdups distribution and liquid holdup hysteresis in a nonwetting two-dimensional (2-D) packed bed. A medical diagnostic X-ray unit has been used to image the local holdups in a 2-D cold model having a random packing of expanded polystyrene beads. An aqueous barium chloride solution was used as a fluid to achieve good contrast on X-ray images. To quantify the local liquid holdup, a simple calibration technique has been developed that can be used for most of the radiological methods such as gamma ray and neutron radiography. The global value of total liquid holdup, obtained by X-ray method, has been compared with two conventional methods: drainage and tracer response. The X-ray technique, after validation, has been used to visualize and quantify, the liquid hysteresis phenomena in a packed bed. The liquid flows in preferred paths or channels that carry droplets/rivulets of increasing size and number as the liquid flow rate is increased. When the flow is reduced, these paths are retained and the higher liquid holdup that persists in these regions leads to the holdup hysteresis effect. Holdup in some regions of the packed bed may be an order of magnitude higher than average at a particular flow rate. (c) 2005 American Institute of Chemical Engineers

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It is well known that rib cage dimensions depend on the gender and vary with the age of the individual. Under this setting it is therefore possible to assume that a computational approach to the problem may be thought out and, consequently, this work will focus on the development of an Artificial Intelligence grounded decision support system to predict individual’s age, based on such measurements. On the one hand, using some basic image processing techniques it were extracted such descriptions from chest X-rays (i.e., its maximum width and height). On the other hand, the computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters for the handling of incomplete, unknown, or even contradictory information. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The accuracy of the proposed model is satisfactory, close to 90%.

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In this study x-ray CT has been used to produce a 3D image of an irradiated PAGAT gel sample, with noise-reduction achieved using the ‘zero-scan’ method. The gel was repeatedly CT scanned and a linear fit to the varying Hounsfield unit of each pixel in the 3D volume was evaluated across the repeated scans, allowing a zero-scan extrapolation of the image to be obtained. To minimise heating of the CT scanner’s x-ray tube, this study used a large slice thickness (1 cm), to provide image slices across the irradiated region of the gel, and a relatively small number of CT scans (63), to extrapolate the zero-scan image. The resulting set of transverse images shows reduced noise compared to images from the initial CT scan of the gel, without being degraded by the additional radiation dose delivered to the gel during the repeated scanning. The full, 3D image of the gel has a low spatial resolution in the longitudinal direction, due to the selected scan parameters. Nonetheless, important features of the dose distribution are apparent in the 3D x-ray CT scan of the gel. The results of this study demonstrate that the zero-scan extrapolation method can be applied to the reconstruction of multiple x-ray CT slices, to provide useful 2D and 3D images of irradiated dosimetry gels.

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The signal-to-noise ratio achievable in x-ray computed tomography (CT) images of polymer gels can be increased by averaging over multiple scans of each sample. However, repeated scanning delivers a small additional dose to the gel which may compromise the accuracy of the dose measurement. In this study, a NIPAM-based polymer gel was irradiated and then CT scanned 25 times, with the resulting data used to derive an averaged image and a "zero-scan" image of the gel. Comparison between these two results and the first scan of the gel showed that the averaged and zero-scan images provided better contrast, higher contrast-to- noise and higher signal-to-noise than the initial scan. The pixel values (Hounsfield units, HU) in the averaged image were not noticeably elevated, compared to the zero-scan result and the gradients used in the linear extrapolation of the zero-scan images were small and symmetrically distributed around zero. These results indicate that the averaged image was not artificially lightened by the small, additional dose delivered during CT scanning. This work demonstrates the broader usefulness of the zero-scan method as a means to verify the dosimetric accuracy of gel images derived from averaged x-ray CT data.

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Présentation: Cet article a été publié dans le journal : Computerised medical imaging and graphics (CMIG). Le but de cet article est de recaler les vertèbres extraites à partir d’images RM avec des vertèbres extraites à partir d’images RX pour des patients scoliotiques, en tenant compte des déformations non-rigides due au changement de posture entre ces deux modalités. À ces fins, une méthode de recalage à l’aide d’un modèle articulé est proposée. Cette méthode a été comparée avec un recalage rigide en calculant l’erreur sur des points de repère, ainsi qu’en calculant la différence entre l’angle de Cobb avant et après recalage. Une validation additionelle de la méthode de recalage présentée ici se trouve dans l’annexe A. Ce travail servira de première étape dans la fusion des images RM, RX et TP du tronc complet. Donc, cet article vérifie l’hypothèse 1 décrite dans la section 3.2.1.

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The registration of pre-operative volumetric datasets to intra- operative two-dimensional images provides an improved way of verifying patient position and medical instrument loca- tion. In applications from orthopedics to neurosurgery, it has a great value in maintaining up-to-date information about changes due to intervention. We propose a mutual information- based registration algorithm to establish the proper align- ment. For optimization purposes, we compare the perfor- mance of the non-gradient Powell method and two slightly di erent versions of a stochastic gradient ascent strategy: one using a sparsely sampled histogramming approach and the other Parzen windowing to carry out probability density approximation. Our main contribution lies in adopting the stochastic ap- proximation scheme successfully applied in 3D-3D registra- tion problems to the 2D-3D scenario, which obviates the need for the generation of full DRRs at each iteration of pose op- timization. This facilitates a considerable savings in compu- tation expense. We also introduce a new probability density estimator for image intensities via sparse histogramming, de- rive gradient estimates for the density measures required by the maximization procedure and introduce the framework for a multiresolution strategy to the problem. Registration results are presented on uoroscopy and CT datasets of a plastic pelvis and a real skull, and on a high-resolution CT- derived simulated dataset of a real skull, a plastic skull, a plastic pelvis and a plastic lumbar spine segment.

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Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

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When patients enter our emergency room with suspected multiple injuries, Statscan provides a full body anterior and lateral image for initial diagnosis, and then zooms in on specific smaller areas for a more detailed evaluation. In order to examine the possible role of Statscan in the management of multiply injured patients we implemented a modified ATLS((R)) algorithm, where X-ray of C-spine, chest and pelvis have been replaced by single-total a.p./lat. body radiograph. Between 15 October 2006 and 1 February 2007 143 trauma patients (mean ISS 15+/-14 (3-75)) were included. We compared the time in resuscitation room to 650 patients (mean ISS 14+/-14 (3-75)) which were treated between 1 January 2002 and 1 January 2004 according to conventional ATLS protocol. The total-body scanning time was 3.5 min (3-6 min) compared to 25.7 (8-48 min) for conventional X-rays, The total ER time was unchanged 28.7 min (13-58 min) compared to 29.1 min (15-65 min) using conventional plain radiography. In 116/143 patients additional CT scans were necessary. In 98/116 full body trauma CT scans were performed. In 18/116 patients selective CT scans were ordered based on Statscan findings. In 43/143 additional conventional X-rays had to be performed, mainly due to inadequate a.p. views of fractured bones. All radiographs were transmitted over the hospital network (Picture Archiving and Communication System, PACS) for immediate simultaneous viewing at different places. The rapid availability of images for interpretation because of their digital nature and the reduced need for repeat exposures because of faulty radiography are also felt to be strengths.

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OBJECTIVES: The aim of this phantom study was to evaluate the contrast-to-noise ratio (CNR) in pulmonary computed tomography (CT)-angiography for 300 and 400 mg iodine/mL contrast media using variable x-ray tube parameters and patient sizes. We also analyzed the possible strategies of dose reduction in patients with different sizes. MATERIALS AND METHODS: The segmental pulmonary arteries were simulated by plastic tubes filled with 1:30 diluted solutions of 300 and 400 mg iodine/mL contrast media in a chest phantom mimicking thick, intermediate, and thin patients. Volume scanning was done with a CT scanner at 80, 100, 120, and 140 kVp. Tube current-time products (mAs) varied between 50 and 120% of the optimal value given by the built-in automatic dose optimization protocol. Attenuation values and CNR for both contrast media were evaluated and compared with the volume CT dose index (CTDI(vol)). Figure of merit, calculated as CNR/CTDIvol, was used to quantify image quality improvement per exposure risk to the patient. RESULTS: Attenuation of iodinated contrast media increased both with decreasing tube voltage and patient size. A CTDIvol reduction by 44% was achieved in the thin phantom with the use of 80 instead of 140 kVp without deterioration of CNR. Figure of merit correlated with kVp in the thin phantom (r = -0.897 to -0.999; P < 0.05) but not in the intermediate and thick phantoms (P = 0.09-0.71), reflecting a decreasing benefit of tube voltage reduction on image quality as the thickness of the phantom increased. Compared with the 300 mg iodine/mL concentration, the same CNR for 400 mg iodine/mL contrast medium was achieved at a lower CTDIvol by 18 to 40%, depending on phantom size and applied tube voltage. CONCLUSIONS: Low kVp protocols for pulmonary embolism are potentially advantageous especially in thin and, to a lesser extent, in intermediate patients. Thin patients profit from low voltage protocols preserving a good CNR at a lower exposure. The use of 80 kVp in obese patients may be problematic because of the limitation of the tube current available, reduced CNR, and high skin dose. The high CNR of the 400 mg iodine/mL contrast medium together with lower tube energy and/or current can be used for exposure reduction.

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During the last few decades, new imaging techniques like X-ray computed tomography have made available rich and detailed information of the spatial arrangement of soil constituents, usually referred to as soil structure. Mathematical morphology provides a plethora of mathematical techniques to analyze and parameterize the geometry of soil structure. They provide a guide to design the process from image analysis to the generation of synthetic models of soil structure in order to investigate key features of flow and transport phenomena in soil. In this work, we explore the ability of morphological functions built over Minkowski functionals with parallel sets of the pore space to characterize and quantify pore space geometry of columns of intact soil. These morphological functions seem to discriminate the effects on soil pore space geometry of contrasting management practices in a Mediterranean vineyard, and they provide the first step toward identifying the statistical significance of the observed differences.

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Fluoroscopic images exhibit severe signal-dependent quantum noise, due to the reduced X-ray dose involved in image formation, that is generally modelled as Poisson-distributed. However, image gray-level transformations, commonly applied by fluoroscopic device to enhance contrast, modify the noise statistics and the relationship between image noise variance and expected pixel intensity. Image denoising is essential to improve quality of fluoroscopic images and their clinical information content. Simple average filters are commonly employed in real-time processing, but they tend to blur edges and details. An extensive comparison of advanced denoising algorithms specifically designed for both signal-dependent noise (AAS, BM3Dc, HHM, TLS) and independent additive noise (AV, BM3D, K-SVD) was presented. Simulated test images degraded by various levels of Poisson quantum noise and real clinical fluoroscopic images were considered. Typical gray-level transformations (e.g. white compression) were also applied in order to evaluate their effect on the denoising algorithms. Performances of the algorithms were evaluated in terms of peak-signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), mean square error (MSE), structural similarity index (SSIM) and computational time. On average, the filters designed for signal-dependent noise provided better image restorations than those assuming additive white Gaussian noise (AWGN). Collaborative denoising strategy was found to be the most effective in denoising of both simulated and real data, also in the presence of image gray-level transformations. White compression, by inherently reducing the greater noise variance of brighter pixels, appeared to support denoising algorithms in performing more effectively. © 2012 Elsevier Ltd. All rights reserved.

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Radiolarians in the Arctic Ocean have been studied lately in both plankton and sediment trap samples in the Chukchi Sea area. These studies have shed light on new radiolarian taxa, especially within the order Entactinaria, including two new species of Joergensenium, Joergensenium arcticum from the western Arctic Ocean, so far restricted to the Pacific Winter Water in the Chukchi Sea, and Joergensenium clevei hitherto found in the northern part of the Norwegian Sea south of the Fram Strait. The taxonomic position of the order Entactinaria is discussed and the genus Joergensenium has been emended. We have also observed in detail the internal structure of J. arcticum using Microfocus X-ray Computed Tomography and have utilized three-dimensional imaging for the first time in a species description.

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X-ray computed tomography (CT) is a medical imaging technique that produces images of trans-axial planes through the human body. When compared with a conventional radiograph, which is an image of many planes superimposed on each other, a CT image exhibits significantly improved contrast although this is at the expense of reduced spatial resolution.----- A CT image is reconstructed mathematically from a large number of one dimensional projections of the chosen plane. These projections are acquired electronically using a linear array of solid-state detectors and an x ray source that rotates around the patient.----- X-ray computed tomography is used routinely in radiological examinations. It has also be found to be useful in special applications such as radiotherapy treatment planning and three-dimensional imaging for surgical planning.

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Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Method: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ‘zero-scan’ image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provides an accurate indication of gel density. Conclusions: It is expected that this work will be utilised in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.

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Sixteen formalin-fixed foetal livers were scanned in vitro using a new system for estimating volume from a sequence of multiplanar 2D ultrasound images. Three different scan techniques were used (radial, parallel and slanted) and four volume estimation algorithms (ellipsoid, planimetry, tetrahedral and ray tracing). Actual liver volumes were measured by water displacement. Twelve of the sixteen livers also received x-ray computed tomography (CT) and magnetic resonance (MR) scans and the volumes were calculated using voxel counting and planimetry. The percentage accuracy (mean ± SD) was 5.3 ± 4.7%, −3.1 ± 9.6% and −0.03 ± 9.7% for ultrasound (radial scans, ray volumes), MR and CT (voxel counting) respectively. The new system may be useful for accurately estimating foetal liver volume in utero.