PubMed Health⌕ Search

SEARCH · PubMed Health

Results for “Data Compression”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29Linked to original sources
PubMed2005

Despeckling of medical ultrasound images using data and rate adaptive lossy compression.

A novel technique for despeckling the medical ultrasound images using lossy compression is presented. The logarithm of the input image is first transformed to the multiscale wavelet domain. It is then shown that the subband coefficients of the log-transformed ultrasound image can be successfully modeled using the generalized Laplacian distribution. Based on this modeling, a simple adaptation of the zero-zone and reconstruction levels of the uniform threshold quantizer is proposed in order to achieve simultaneous despeckling and quantization. This adaptation is based on: (1) an estimate of the corrupting speckle noise level in the image; (2) the estimated statistics of the noise-free subband coefficients; and (3) the required compression rate. The Laplacian distribution is considered as a special case of the generalized Laplacian distribution and its efficacy is demonstrated for the problem under consideration. Context-based classification is also applied to the noisy coefficients to enhance the performance of the subband coder. Simulation results using a contrast detail phantom image and several real ultrasound images are presented. To validate the performance of the proposed scheme, comparison with two two-stage schemes, wherein the speckled image is first filtered and then compressed using the state-of-the-art JPEG2000 encoder, is presented. Experimental results show that the proposed scheme works better, both in terms of the signal to noise ratio and the visual quality.

Algorithms↗
PubMed1995

A model for acute, chronic, and delayed graded compression of the dog cauda equina. Neurophysiologic and histologic changes induced by acute, graded compression.

STUDY DESIGN: The results of acute compression on nerve function and morphology were analyzed in a recently developed model for graded cauda equina compression in the dog. OBJECTIVES: The model was developed to better mimic the clinical situation of cauda equina compression in association with spinal canal stenosis. SUMMARY OF BACKGROUND DATA: The compression of the cauda equina has been induced by metal clips, plastic bands, constrictors, and inflatable balloons. No model has used the intact spinal canal and induced compression by increasing the pressure per se in the canal. METHODS: An inflatable balloon with a diameter exceeding the diameter of the spinal canal was placed under the lamina of the L7 vertebra in the dog. The balloon was inflated to various pressures, and muscle action potential area and nerve conduction velocity were monitored during 2 hours of compression and 1.5 hours of recovery. Nerve root specimens were processed for light microscopic examination. RESULTS: There was a progressive reduction of muscle action potential area and nerve conduction velocity that was proportional to the applied pressure. Histologic evaluation revealed no nerve fiber damage but a slight intraneural edema after compression at 200 mg Hg. CONCLUSIONS: The presented model may provide reproducible results regarding neurophysiologic and morphologic effects after acute, graded compression of the dog cauda equina. Two additional conclusions can be made from this study. First, the area measurement of the MAP is probably well suited for recordings and analyses of changes in muscle action potentials. Second, the specific onset rate of this study, in relation to previous studies, indicates that there is a threshold for the compression onset rate for inducing additional nerve injury located in the interval 0.1-0.8 seconds. The results from the present study provides important baseline data for the continued studies on chronic and intermittent compression with the compression model.

Action Potentials↗
PubMed2006

A joint source-channel distortion model for JPEG compressed images.

The need for efficient joint source-channel coding (JSCC) is growing as new multimedia services are introduced in commercial wireless communication systems. An important component of practical JSCC schemes is a distortion model that can predict the quality of compressed digital multimedia such as images and videos. The usual approach in the JSCC literature for quantifying the distortion due to quantization and channel errors is to estimate it for each image using the statistics of the image for a given signal-to-noise ratio (SNR). This is not an efficient approach in the design of real-time systems because of the computational complexity. A more useful and practical approach would be to design JSCC techniques that minimize average distortion for a large set of images based on some distortion model rather than carrying out per-image optimizations. However, models for estimating average distortion due to quantization and channel bit errors in a combined fashion for a large set of images are not available for practical image or video coding standards employing entropy coding and differential coding. This paper presents a statistical model for estimating the distortion introduced in progressive JPEG compressed images due to quantization and channel bit errors in a joint manner. Statistical modeling of important compression techniques such as Huffman coding, differential pulse-coding modulation, and run-length coding are included in the model. Examples show that the distortion in terms of peak signal-to-noise ratio (PSNR) can be predicted within a 2-dB maximum error over a variety of compression ratios and bit-error rates. To illustrate the utility of the proposed model, we present an unequal power allocation scheme as a simple application of our model. Results show that it gives a PSNR gain of around 6.5 dB at low SNRs, as compared to equal power allocation.

Algorithms↗
PubMed2006

Quality assessment of ECG compression techniques using a wavelet-based diagnostic measure.

Electrocardiograph (ECG) compression techniques are gaining momentum due to the huge database requirements and wide band communication channels needed to maintain high quality ECG transmission. Advances in computer software and hardware enable the birth of new techniques in ECG compression, aiming at high compression rates. In general, most of the introduced ECG compression techniques depend on their evaluation performance on either inaccurate measures or measures targeting random behavior of error. In this paper, a new wavelet-based quality measure is proposed. A new wavelet-based quality measure is proposed. The new approach is based on decomposing the segment of interest into frequency bands where a weighted score is given to the band depending on its dynamic range and its diagnostic significance. A performance evaluation of the measure is conducted quantitatively and qualitatively. Comparative results with existing quality measures show that the new measure is insensitive to error variation, is accurate, and correlates very well with subjective tests.

Algorithms↗
PubMed2006

A range/domain approximation error-based approach for fractal image compression.

Fractals can be an effective approach for several applications other than image coding and transmission: database indexing, texture mapping, and even pattern recognition problems such as writer authentication. However, fractal-based algorithms are strongly asymmetric because, in spite of the linearity of the decoding phase, the coding process is much more time consuming. Many different solutions have been proposed for this problem, but there is not yet a standard for fractal coding. This paper proposes a method to reduce the complexity of the image coding phase by classifying the blocks according to an approximation error measure. It is formally shown that postponing range\slash domain comparisons with respect to a preset block, it is possible to reduce drastically the amount of operations needed to encode each range. The proposed method has been compared with three other fractal coding methods, showing under which circumstances it performs better in terms of both bit rate and/or computing time.

Algorithms↗