91 resultados para Image acquisition and representation


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PURPOSE: The aim of this study was to investigate the effect of magnetization transfer on multislice T(1) and T(2) measurements of articular cartilage. MATERIALS AND METHODS: A set of phantoms with different concentrations of collagen and contrast agent (Gd-DTPA(2-)) were used for the in vitro study. A total of 20 healthy knees were used for the in vivo study. T(1) and T(2) measurements were performed using fast-spin-echo inversion-recovery (FSE-IR) sequence and multi-spin-echo (MSE) sequence, respectively, in both in vitro and in vivo studies. We investigated the difference in T(1) and T(2) values between that measured by single-slice acquisition and that measured by multislice acquisition. RESULTS: Regarding T(1) measurement, a large drop of T(1) in all slices and also a large interslice variation in T(1) were observed when multislice acquisition was used. Regarding T(2) measurement, a substantial drop of T(2) in all slices was observed; however, there was no apparent interslice variation when multislice acquisition was used. CONCLUSION: This study demonstrated that the adaptation of multislice acquisition technique for T(1) measurement using FSE-IR methodology is difficult and its use for clinical evaluation is problematic. In contrast, multislice acquisition for T(2) measurement using MSE was clinically applicable if inaccuracies caused by multislice acquisition were taken into account. J. Magn. Reson. Imaging 2007;26:109-117. (c) 2007 Wiley-Liss, Inc.

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The verification possibilities of dynamically collimated treatment beams with a scanning liquid ionization chamber electronic portal image device (SLIC-EPID) are investigated. The ion concentration in the liquid of a SLIC-EPID and therefore the read-out signal is determined by two parameters of a differential equation describing the creation and recombination of the ions. Due to the form of this equation, the portal image detector describes a nonlinear dynamic system with memory. In this work, the parameters of the differential equation were experimentally determined for the particular chamber in use and for an incident open 6 MV photon beam. The mathematical description of the ion concentration was then used to predict portal images of intensity-modulated photon beams produced by a dynamic delivery technique, the sliding window approach. Due to the nature of the differential equation, a mathematical condition for 'reliable leaf motion verification' in the sliding window technique can be formulated. It is shown that the time constants for both formation and decay of the equilibrium concentration in the chamber is in the order of seconds. In order to guarantee reliable leaf motion verification, these time constants impose a constraint on the rapidity of the image-read out for a given maximum leaf speed. For a leaf speed of 2 cm s(-1), a minimum image acquisition frequency of about 2 Hz is required. Current SLIC-EPID systems are usually too slow since they need about a second to acquire a portal image. However, if the condition is fulfilled, the memory property of the system can be used to reconstruct the leaf motion. It is shown that a simple edge detecting algorithm can be employed to determine the leaf positions. The method is also very robust against image noise.

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In external beam radiotherapy, electronic portal imaging becomes more and more an indispensable tool for the verification of the patient setup. For the safe clinical introduction of high dose conformal radiotherapy like intensity modulated radiation therapy, on-line patient setup verification is a prerequisite to ensure that the planned dosimetric coverage of the tumor volume is actually realized in the patient. Since the direction of setup fields often deviates from the direction of the treatment beams, extra dose is delivered to the patient during the acquisition of these portal images which may reach clinical relevance. The aim of this work was to develop a new acquisition mode for the PortalVision aS500 electronic portal imaging device from Varian Medical Systems that allows one to take portal images with reduced dose while keeping good image quality. The new acquisition mode, called RadMode, selectively enables and disables beam pulses during image acquisition allowing one to stop wasting valuable dose during the initial acquisition of "reset frames." Images of excellent quality can be taken with 1 MU only. This low dose per image facilitates daily setup verification with considerably reduced extra dose.

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PURPOSE: The aim of this study is to implement augmented reality in real-time image-guided interstitial brachytherapy to allow an intuitive real-time intraoperative orientation. METHODS AND MATERIALS: The developed system consists of a common video projector, two high-resolution charge coupled device cameras, and an off-the-shelf notebook. The projector was used as a scanning device by projecting coded-light patterns to register the patient and superimpose the operating field with planning data and additional information in arbitrary colors. Subsequent movements of the nonfixed patient were detected by means of stereoscopically tracking passive markers attached to the patient. RESULTS: In a first clinical study, we evaluated the whole process chain from image acquisition to data projection and determined overall accuracy with 10 patients undergoing implantation. The described method enabled the surgeon to visualize planning data on top of any preoperatively segmented and triangulated surface (skin) with direct line of sight during the operation. Furthermore, the tracking system allowed dynamic adjustment of the data to the patient's current position and therefore eliminated the need for rigid fixation. Because of soft-part displacement, we obtained an average deviation of 1.1 mm by moving the patient, whereas changing the projector's position resulted in an average deviation of 0.9 mm. Mean deviation of all needles of an implant was 1.4 mm (range, 0.3-2.7 mm). CONCLUSIONS: The developed low-cost augmented-reality system proved to be accurate and feasible in interstitial brachytherapy. The system meets clinical demands and enables intuitive real-time intraoperative orientation and monitoring of needle implantation.

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The purpose of this retrospective study was to intra-individually compare the image quality of computed radiography (CR) and low-dose linear-slit digital radiography (LSDR) for supine chest radiographs. A total of 90 patients (28 female, 62 male; mean age, 55.1 years) imaged with CR and LSDR within a mean time interval of 2.8 days +/- 3.0 were included in this study. Two independent readers evaluated the image quality of CR and LSDR based on modified European Guidelines for Quality Criteria for chest X-ray. The Wilcoxon test was used to analyse differences between the techniques. The overall image quality of LSDR was significantly better than the quality of CR (9.75 vs 8.16 of a maximum score of 10; p < 0.001). LSDR performed significantly better than CR for delineation of anatomical structures in the mediastinum and the retrocardiac lung (p < 0.001). CR was superior to LSDR for visually sharp delineation of the lung vessels and the thin linear structures in the lungs. We conclude that LSDR yields better image quality and may be more suitable for excluding significant pathological features of the chest in areas with high attenuation compared with CR.

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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

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PURPOSE Positron emission tomography (PET)∕computed tomography (CT) measurements on small lesions are impaired by the partial volume effect, which is intrinsically tied to the point spread function of the actual imaging system, including the reconstruction algorithms. The variability resulting from different point spread functions hinders the assessment of quantitative measurements in clinical routine and especially degrades comparability within multicenter trials. To improve quantitative comparability there is a need for methods to match different PET∕CT systems through elimination of this systemic variability. Consequently, a new method was developed and tested that transforms the image of an object as produced by one tomograph to another image of the same object as it would have been seen by a different tomograph. The proposed new method, termed Transconvolution, compensates for differing imaging properties of different tomographs and particularly aims at quantitative comparability of PET∕CT in the context of multicenter trials. METHODS To solve the problem of image normalization, the theory of Transconvolution was mathematically established together with new methods to handle point spread functions of different PET∕CT systems. Knowing the point spread functions of two different imaging systems allows determining a Transconvolution function to convert one image into the other. This function is calculated by convolving one point spread function with the inverse of the other point spread function which, when adhering to certain boundary conditions such as the use of linear acquisition and image reconstruction methods, is a numerically accessible operation. For reliable measurement of such point spread functions characterizing different PET∕CT systems, a dedicated solid-state phantom incorporating (68)Ge∕(68)Ga filled spheres was developed. To iteratively determine and represent such point spread functions, exponential density functions in combination with a Gaussian distribution were introduced. Furthermore, simulation of a virtual PET system provided a standard imaging system with clearly defined properties to which the real PET systems were to be matched. A Hann window served as the modulation transfer function for the virtual PET. The Hann's apodization properties suppressed high spatial frequencies above a certain critical frequency, thereby fulfilling the above-mentioned boundary conditions. The determined point spread functions were subsequently used by the novel Transconvolution algorithm to match different PET∕CT systems onto the virtual PET system. Finally, the theoretically elaborated Transconvolution method was validated transforming phantom images acquired on two different PET systems to nearly identical data sets, as they would be imaged by the virtual PET system. RESULTS The proposed Transconvolution method matched different PET∕CT-systems for an improved and reproducible determination of a normalized activity concentration. The highest difference in measured activity concentration between the two different PET systems of 18.2% was found in spheres of 2 ml volume. Transconvolution reduced this difference down to 1.6%. In addition to reestablishing comparability the new method with its parameterization of point spread functions allowed a full characterization of imaging properties of the examined tomographs. CONCLUSIONS By matching different tomographs to a virtual standardized imaging system, Transconvolution opens a new comprehensive method for cross calibration in quantitative PET imaging. The use of a virtual PET system restores comparability between data sets from different PET systems by exerting a common, reproducible, and defined partial volume effect.

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Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

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AIM To compare image quality and diagnostic confidence of 100 kVp CT pulmonary angiography (CTPA) in patients with body weights (BWs) below and above 100kg. MATERIALS AND METHODS The present retrospective study comprised 216 patients (BWs of 75-99kg, 114 patients; 100-125kg, 88 patients; >125kg, 14 patients), who received 100 kVp CTPA to exclude pulmonary embolism. The attenuation was measured and the contrast-to-noise ratio (CNR) was calculated in the pulmonary trunk. Size-specific dose estimates (SSDEs) were evaluated. Three blinded radiologists rated subjective image quality and diagnostic confidence. Results between the BW groups and between three body mass index (BMI) groups (BMI <25kg/m(2), BMI = 25-29.9kg/m(2), and BMI ≥30kg/m(2), i.e., normal weight, overweight, and obese patients) were compared using the Kruskal-Wallis test. RESULTS Vessel attenuation was higher and SDDE was lower in the 75-99kg group than at higher BWs (p-values between <0.001 and 0.03), with no difference between the 100-125 and >125kg groups (p = 0.892 and 1). Subjective image quality and diagnostic confidence were not different among the BW groups (p = 0.225 and 1). CNR was lower (p < 0.006) in obese patients than in normal weight or overweight subjects. Diagnostic confidence was not different in the BMI groups (p = 0.105). CONCLUSION CTPA at 100 kVp tube voltage can be used in patients weighing up to 125kg with no significant deterioration of subjective image quality and confidence. The applicability of 100 kVp in the 125-150kg BW range needs further testing in larger collectives.

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OBJECTIVES To find a threshold body weight (BW) below 100 kg above which computed tomography pulmonary angiography (CTPA) using reduced radiation and a reduced contrast material (CM) dose provides significantly impaired quality and diagnostic confidence compared with standard-dose CTPA. METHODS In this prospectively randomised study of 501 patients with suspected pulmonary embolism and BW <100 kg, 246 were allocated into the low-dose group (80 kVp, 75 ml CM) and 255 into the normal-dose group (100 kVp, 100 ml CM). Contrast-to-noise ratio (CNR) in the pulmonary trunk was calculated. Two blinded chest radiologists independently evaluated subjective image quality and diagnostic confidence. Data were compared between the normal-dose and low-dose groups in five BW subgroups. RESULTS Vessel attenuation did not differ between the normal-dose and low-dose groups within each BW subgroup (P = 1.0). The CNR was higher with the normal-dose compared with the low-dose protocol (P < 0.006) in all BW subgroups except for the 90-99 kg subgroup (P = 0.812). Subjective image quality and diagnostic confidence did not differ between CT protocols in all subgroups (P between 0.960 and 1.0). CONCLUSIONS Subjective image quality and diagnostic confidence with 80 kVp CTPA is not different from normal-dose protocol in any BW group up to 100 kg. KEY POINTS • 80 kVp CTPA is safe in patients weighing <100 kg • Reduced radiation and iodine dose still provide high vessel attenuation • Image quality and diagnostic confidence with low-dose CTPA is good • Diagnostic confidence does not deteriorate in obese patients weighing <100 kg.

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Two-dimensional (2D) crystallisation of Membrane proteins reconstitutes them into their native environment, the lipid bilayer. Electron crystallography allows the structural analysis of these regular protein–lipid arrays up to atomic resolution. The crystal quality depends on the protein purity, ist stability and on the crystallisation conditions. The basics of 2D crystallisation and different recent advances are reviewed and electron crystallography approaches summarised. Progress in 2D crystallisation, sample preparation, image detectors and automation of the data acquisition and processing pipeline makes 2D electron crystallography particularly attractive for the structural analysis of membrane proteins that are too small for single-particle analyses and too unstable to form three-dimensional (3D) crystals.

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Spinal image analysis and computer assisted intervention have emerged as new and independent research areas, due to the importance of treatment of spinal diseases, increasing availability of spinal imaging, and advances in analytics and navigation tools. Among others, multiple modality spinal image analysis and spinal navigation tools have emerged as two keys in this new area. We believe that further focused research in these two areas will lead to a much more efficient and accelerated research path, avoiding detours that exist in other applications, such as in brain and heart.

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The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).

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An algorithm for the real-time registration of a retinal video sequence captured with a scanning digital ophthalmoscope (SDO) to a retinal composite image is presented. This method is designed for a computer-assisted retinal laser photocoagulation system to compensate for retinal motion and hence enhance the accuracy, speed, and patient safety of retinal laser treatments. The procedure combines intensity and feature-based registration techniques. For the registration of an individual frame, the translational frame-to-frame motion between preceding and current frame is detected by normalized cross correlation. Next, vessel points on the current video frame are identified and an initial transformation estimate is constructed from the calculated translation vector and the quadratic registration matrix of the previous frame. The vessel points are then iteratively matched to the segmented vessel centerline of the composite image to refine the initial transformation and register the video frame to the composite image. Criteria for image quality and algorithm convergence are introduced, which assess the exclusion of single frames from the registration process and enable a loss of tracking signal if necessary. The algorithm was successfully applied to ten different video sequences recorded from patients. It revealed an average accuracy of 2.47 ± 2.0 pixels (∼23.2 ± 18.8 μm) for 2764 evaluated video frames and demonstrated that it meets the clinical requirements.