1000 resultados para Holographic images


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Objective: The aim of this study was to evaluate the performances of observers in diagnosing proximal caries in digital images obtained from digital bitewing radiographs using two scanners and four digital cameras in Joint Photographic Experts Group (JPEG) and tagged image file format (TIFF) files, and comparing them with the original conventional radiographs. Method: In total, 56 extracted teeth were radiographed with Kodak Insight film (Eastman Kodak, Rochester, NY) in a Kaycor Yoshida X-ray device (Kaycor X-707;Yoshida Dental Manufacturing Co., Tokyo, Japan) operating at 70 kV and 7 mA with an exposure time of 0.40 s. The radiographs were obtained and scanned by CanonScan D646U (Canon USA Inc., Newport News, VA) and Genius ColorPage HR7X (KYE Systems Corp. America, Doral, FL) scanners, and by Canon Powershot G2 (Canon USA Inc.), Canon RebelXT (Canon USA Inc.), Nikon Coolpix 8700 (Nikon Inc., Melville, NY), and Nikon D70s (Nikon Inc.) digital cameras in JPEG and TIFF formats. Three observers evaluated the images. The teeth were then observed under the microscope in polarized light for the verification of the presence and depth of the carious lesions. Results: The probability of no diagnosis ranged from 1.34% (Insight film) to 52.83% (CanonScan/JPEG). The sensitivity ranged from 0.24 (Canon RebelXT/JPEG) to 0.53 (Insight film), the specificity ranged from 0.93 (Nikon Coolpix/JPEG, Canon Powershot/TIFF, Canon RebelXT/JPEG and TIFF) to 0.97 (CanonScan/TIFF and JPEG) and the accuracy ranged from 0.82 (Canon RebelXT/JPEG) to 0.91 (CanonScan/JPEG). Conclusion: The carious lesion diagnosis did not change in either of the file formats (JPEG and TIFF) in which the images were saved for any of the equipment used. Only the CanonScan scanner did not have adequate performance in radiography digitalization for caries diagnosis and it is not recommended for this purpose. Dentomaxillofacial Radiology (2011) 40, 338-343. doi: 10.1259/dmfr/67185962

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Near-Resonant Holographic Interferometry is a powerful technique which extends the established advantages of conventional holographic interferometry by allowing a species-specific number density to be determined. It has been tested in the harsh flow conditions generated in a high enthalpy facility yielding information about the shock shape on a cylindrical body and on the distribution of a trace species seeded into the flow.

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Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.

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We compared the quality of realtime fetal ultrasound images transmitted using ISDN and IP networks. Four experienced obstetric ultrasound specialists viewed standard recordings in a randomized trial and rated the appearance of 30 fetal anatomical landmarks, each on a seven-point scale. A total of 12 evaluations were performed for various combinations of bandwidths (128, 384 or 768 kbit/s) and networks (ISDN or IF). The intraobserver coefficient of variation was 2.9%, 5.0%, 12.7% and 14.7% for the four observers. The mean overall ratings by each of the four observers were 4.6, 4.8, 5.0 and 5.3, respectively (a rating of 4 indicated satisfactory visualization and 7 indicated as good as the original recording). Analysis of variance showed that there were no significant interobserver variations nor significant differences in the mean scores for the different types of videoconferencing machines used. The most significant variable affecting the mean score was the bandwidth used. For ISDN, the mean score was 3.7 at 128 kbit/s, which was significantly worse than the mean score of 4.9 at 384 kbit/s, which was in turn significantly worse than the mean score of 5.9 at 768 kbit/s. The mean score for transmission using IP was about 0.5 points lower than that using ISDN across all the different bandwidths, but the differences were not significant. It appears that IP transmission in a private (non-shared) network is an acceptable alternative to ISDN for fetal tele-ultrasound and one deserving further study.

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This paper traces fluctuating attitudes to Islam and its Prophet, particularly in the eighteenth and nineteenth. Western perceptions, as revealed by writers of the period, encyclopaedias, biographies and commentaries, were sometimes sympathetic, sometimes dismissive; sometimes celebrating Islam's piousness; sometimes accusing it of fraud. Sometimes Islam is seen as benign; sometimes its violence is seen as endemic. Often the cultural biases of western observers are obvious: the west is progressive and historically dominant, the east (and its cultural accoutrements) is degenerate and over-zealous. But we ought not judge religions or cultures by their worst manifestations alone. Oriental societies were never just Islamic or traditional. They comprise not only those who perpetuate oppressive practices towards women but also modernizers who seek change.

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Deterioration of concrete or reinforcing steel through excessive contaminant concentration is often the result of repeated wetting and drying cycles. At each cycle, the absorption of water carries new contaminants into the unsaturated concrete. Nuclear Magnetic Resonance (NMR) is used with large concrete samples to observe the shape of the wetting profile during a simple one-dimensional wetting process. The absorption of water by dry concrete is modelled by a nonlinear diffusion equation with the unsaturated hydraulic diffusivity being a strongly nonlinear function of the moisture content. Exponential and power functions are used for the hydraulic diffusivity and corresponding solutions of the diffusion equation adequately predict the shape of the experimental wetting profile. The shape parameters, describing the wetting profile, vary little between different blends and are relatively insensitive to subsequent re-wetting experiments allowing universal parameters to be suggested for these concretes.

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Pectus excavatum is the most common congenital deformity of the anterior thoracic wall. The surgical correction of such deformity, using Nuss procedure, consists in the placement of a personalized convex prosthesis into sub-sternal position to correct the deformity. The aim of this work is the CT-scan substitution by ultrasound imaging for the pre-operative diagnosis and pre-modeling of the prosthesis, in order to avoid patient radiation exposure. To accomplish this, ultrasound images are acquired along an axial plane, followed by a rigid registration method to obtain the spatial transformation between subsequent images. These images are overlapped to reconstruct an axial plane equivalent to a CT-slice. A phantom was used to conduct preliminary experiments and the achieved results were compared with the corresponding CT-data, showing that the proposed methodology can be capable to create a valid approximation of the anterior thoracic wall, which can be used to model/bend the prosthesis

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Background: Regulating mechanisms of branching morphogenesis of fetal lung rat explants have been an essential tool for molecular research. This work presents a new methodology to accurately quantify the epithelial, outer contour and peripheral airway buds of lung explants during cellular development from microscopic images. Methods: The outer contour was defined using an adaptive and multi-scale threshold algorithm whose level was automatically calculated based on an entropy maximization criterion. The inner lung epithelial was defined by a clustering procedure that groups small image regions according to the minimum description length principle and local statistical properties. Finally, the number of peripheral buds were counted as the skeleton branched ends from a skeletonized image of the lung inner epithelial. Results: The time for lung branching morphometric analysis was reduced in 98% in contrast to the manual method. Best results were obtained in the first two days of cellular development, with lesser standard deviations. Non-significant differences were found between the automatic and manual results in all culture days. Conclusions: The proposed method introduces a series of advantages related to its intuitive use and accuracy, making the technique suitable to images with different lightning characteristics and allowing a reliable comparison between different researchers.

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Dental implant recognition in patients without available records is a time-consuming and not straightforward task. The traditional method is a complete user-dependent process, where the expert compares a 2D X-ray image of the dental implant with a generic database. Due to the high number of implants available and the similarity between them, automatic/semi-automatic frameworks to aide implant model detection are essential. In this study, a novel computer-aided framework for dental implant recognition is suggested. The proposed method relies on image processing concepts, namely: (i) a segmentation strategy for semi-automatic implant delineation; and (ii) a machine learning approach for implant model recognition. Although the segmentation technique is the main focus of the current study, preliminary details of the machine learning approach are also reported. Two different scenarios are used to validate the framework: (1) comparison of the semi-automatic contours against implant’s manual contours of 125 X-ray images; and (2) classification of 11 known implants using a large reference database of 601 implants. Regarding experiment 1, 0.97±0.01, 2.24±0.85 pixels and 11.12±6 pixels of dice metric, mean absolute distance and Hausdorff distance were obtained, respectively. In experiment 2, 91% of the implants were successfully recognized while reducing the reference database to 5% of its original size. Overall, the segmentation technique achieved accurate implant contours. Although the preliminary classification results prove the concept of the current work, more features and an extended database should be used in a future work.

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In daily cardiology practice, assessment of left ventricular (LV) global function using non-invasive imaging remains central for the diagnosis and follow-up of patients with cardiovascular diseases. Despite the different methodologies currently accessible for LV segmentation in cardiac magnetic resonance (CMR) images, a fast and complete LV delineation is still limitedly available for routine use. In this study, a localized anatomically constrained affine optical flow method is proposed for fast and automatic LV tracking throughout the full cardiac cycle in short-axis CMR images. Starting from an automatically delineated LV in the end-diastolic frame, the endocardial and epicardial boundaries are propagated by estimating the motion between adjacent cardiac phases using optical flow. In order to reduce the computational burden, the motion is only estimated in an anatomical region of interest around the tracked boundaries and subsequently integrated into a local affine motion model. Such localized estimation enables to capture complex motion patterns, while still being spatially consistent. The method was validated on 45 CMR datasets taken from the 2009 MICCAI LV segmentation challenge. The proposed approach proved to be robust and efficient, with an average distance error of 2.1 mm and a correlation with reference ejection fraction of 0.98 (1.9 ± 4.5%). Moreover, it showed to be fast, taking 5 seconds for the tracking of a full 4D dataset (30 ms per image). Overall, a novel fast, robust and accurate LV tracking methodology was proposed, enabling accurate assessment of relevant global function cardiac indices, such as volumes and ejection fraction.

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The use of iris recognition for human authentication has been spreading in the past years. Daugman has proposed a method for iris recognition, composed by four stages: segmentation, normalization, feature extraction, and matching. In this paper we propose some modifications and extensions to Daugman's method to cope with noisy images. These modifications are proposed after a study of images of CASIA and UBIRIS databases. The major modification is on the computationally demanding segmentation stage, for which we propose a faster and equally accurate template matching approach. The extensions on the algorithm address the important issue of pre-processing that depends on the image database, being mandatory when we have a non infra-red camera, like a typical WebCam. For this scenario, we propose methods for reflection removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images show that the template matching segmentation method is more accurate and faster than the previous one, for noisy images. The proposed algorithms are found to be efficient and necessary when we deal with non infra-red images and non uniform illumination.

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The rapid growth in genetics and molecular biology combined with the development of techniques for genetically engineering small animals has led to increased interest in in vivo small animal imaging. Small animal imaging has been applied frequently to the imaging of small animals (mice and rats), which are ubiquitous in modeling human diseases and testing treatments. The use of PET in small animals allows the use of subjects as their own control, reducing the interanimal variability. This allows performing longitudinal studies on the same animal and improves the accuracy of biological models. However, small animal PET still suffers from several limitations. The amounts of radiotracers needed, limited scanner sensitivity, image resolution and image quantification issues, all could clearly benefit from additional research. Because nuclear medicine imaging deals with radioactive decay, the emission of radiation energy through photons and particles alongside with the detection of these quanta and particles in different materials make Monte Carlo method an important simulation tool in both nuclear medicine research and clinical practice. In order to optimize the quantitative use of PET in clinical practice, data- and image-processing methods are also a field of intense interest and development. The evaluation of such methods often relies on the use of simulated data and images since these offer control of the ground truth. Monte Carlo simulations are widely used for PET simulation since they take into account all the random processes involved in PET imaging, from the emission of the positron to the detection of the photons by the detectors. Simulation techniques have become an importance and indispensable complement to a wide range of problems that could not be addressed by experimental or analytical approaches.