[Medullary compression caused by Paget's disease of the spine].
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A digital radiological image is made by a number of pixels, each of them characterized by a definite numerical value obtained by quantization which represents the luminance in that specific image unit. Spatial resolution and dynamic range are the main factors in determining the quality of a digital radiological image. The product of the two above factors defines the global dimensions of the image and is expressed in bits. In conventional radiographic images the global dimension of the image is expressed in MBytes, because of its high spatial and contrast resolution. To reduce the visualization and storage requirements as well as the transmission time of large image data sets, compression algorithms have been recently introduced. These algorithms are based on the fact that often in a digital image parts of the binary data are "redundant", that is they are not necessary for correct image representation. Therefore, compression methods are aimed at reducing both statistical and perceptive redundancy. Statistical redundancy is reduced by means of lossless coding which does not allow to compress images with a ratio higher than 4-5:1 and that--by definition--allows to recover the original image quality. On the other hand "lossy" compression algorithms, which eliminate the perceptive redundancy, are based on the reduction of spatial resolution and dynamic range and on transform-based methods. In particular, the latter have usually been more successful in terms of efficient compression, even when applied to conventional radiographic images. The basic transform procedure can be modified at various levels. JPEG is one of these methods, originally developed for photographic images, which can be usefully applied to radiological images as well. Lossy procedures allow to reach higher compression ratios than lossless methods, but the decrease in information content must be prevented from reducing diagnostic accuracy. In order to assess the diagnostic efficiency of the images compressed with lossy methods, semi-objective analyses are usually performed and ROC curves are produced and evaluated. A model ROC analysis is presented.
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By considering the blood as a mixture of ultrafiltrate and protein concentrate, the additive nature of compressibility and density from the components is utilized to deduce a linear relation between the compressibility and density for blood. This deduction also indicates that the intercept and slope of the linear relation are independent of the hematocrit, plasma protein concentration, and hemoglobin concentration of red blood cells. To verify experimentally this linear relation, saline and plasma dilutions on porcine or canine blood flowing in an extracorporeal circuit were carried out. The hematocrit of the experiments ranges from 0% to 55% and the plasma protein concentration ranges from 10 to 90 g/l. A resonance device in the circuit measured the density rhob of blood at 37 degrees C and an ultrasound system measured the sound velocity cb. The range of density is from 1,010 to 1,060 g/l and that of sound velocity is from 1,530 to 1,580 m/s. The linear relation that best fits the data of compressibility [computed as (rhob cb(2))-1] and density has a correlation coefficient of 0.9978. The linear relation is found to fit well the dependence of compressibility on density derived from the sound velocity data of human, horse, and porcine blood in the literature.
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Perfect reconstruction, quality scalability, and region-of-interest coding are basic features needed for the image compression schemes used in telemedicine applications. This paper proposes a new wavelet-based embedded compression technique that efficiently exploits the intraband dependencies and uses a quadtree-based approach to encode the significance maps. The algorithm produces a losslessly compressed embedded data stream, supports quality scalability, and permits region-of-interest coding. Moreover, experimental results obtained on various images show that the proposed algorithm provides competitive lossless/lossy compression results. The proposed technique is well suited for telemedicine applications that require fast interactive handling of large image sets, over networks with limited and/or variable bandwidth.
The paper reports a kind of new compression method of ECG signal. The method is realized by means of wavelet packets transform based on best basis performed by Shanon-Weaker entropy criterion. The result of simulation shows that this is an efficient compression method characterized by larger compression ratio and less loss, and the original signal can be recovered well.
A portable external pneumatic intermittent compression (EPIC) device has been successful in reducing peripheral edema. This study explored the effectiveness of EPIC for treating dependent pregnancy edema. In the study, 42 healthy pregnant women received EPIC for 30 minutes at 40 torr while in the left lateral recumbent position: Group One with mid-thigh boots, and Group Two with below-knee boots. Prior to compression, descriptive data were gathered, leg circumference measurements made, and surface skin temperatures recorded for three sites per leg. Vital signs were taken and pedal edema subjectively indexed. Following compression, circumferences, skin temperatures, vital signs, and edema indices were rerecorded. Three volumes were calculated for each leg using a mathematical model of leg segments as conical frustum units. Mean volume reductions for each leg were significant. The mid-thigh-length boots produced greater mean volume decreases. The volume decrease for calf, lower leg, and foot frustum units were significant. EPIC holds promise as a useful treatment for dependent pregnancy edema.
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