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PubMed2006

Medical image compression using DCT-based subband decomposition and modified SPIHT data organization.

OBJECTIVE: The work proposed a novel bit-rate-reduced approach for reducing the memory required to store a remote diagnosis and rapidly transmission it. METHOD: In the work, an 8x8 Discrete Cosine Transform (DCT) approach is adopted to perform subband decomposition. Modified set partitioning in hierarchical trees (SPIHT) is then employed to organize data and entropy coding. The translation function can store the detailed characteristics of an image. A simple transformation to obtain DCT spectrum data in a single frequency domain decomposes the original signal into various frequency domains that can further compressed by wavelet-based algorithm. In this scheme, insignificant DCT coefficients that correspond to a particular spatial location in the high-frequency subbands can be employed to reduce redundancy by applying a proposed combined function in association with the modified SPIHT. RESULTS AND CONCLUSIONS: Simulation results showed that the embedded DCT-CSPIHT image compression reduced the computational complexity to only a quarter of the wavelet-based subband decomposition, and improved the quality of the reconstructed medical image as given by both the peak signal-to-noise ratio (PSNR) and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate. Additionally, since 8x8 fast DCT hardware implementation being commercially available, the proposed DCT-CSPIHT can perform well in high speed image coding and transmission.

Algorithms↗
PubMed2005

Ultrasonic data compression via parameter estimation.

Ultrasonic imaging in medical and industrial applications often requires a large amount of data collection. Consequently, it is desirable to use data compression techniques to reduce data and to facilitate the analysis and remote access of ultrasonic information. The precise data representation is paramount to the accurate analysis of the shape, size, and orientation of ultrasonic reflectors, as well as to the determination of the properties of the propagation path. In this study, a successive parameter estimation algorithm based on a modified version of the continuous wavelet transform (CWT) to compress and denoise ultrasonic signals is presented. It has been shown analytically that the CWT (i.e., time x frequency representation) yields an exact solution for the time-of-arrival and a biased solution for the center frequency. Consequently, a modified CWT (MCWT) based on the Gabor-Helstrom transform is introduced as a means to exactly estimate both time-of-arrival and center frequency of ultrasonic echoes. Furthermore, the MCWT also has been used to generate a phase x bandwidth representation of the ultrasonic echo. This representation allows the exact estimation of the phase and the bandwidth. The performance of this algorithm for data compression and signal analysis is studied using simulated and experimental ultrasonic signals. The successive parameter estimation algorithm achieves a data compression ratio of (1-5N/J), where J is the number of samples and N is the number of echoes in the signal. For a signal with 10 echoes and 2048 samples, a compression ratio of 96% is achieved with a signal-to-noise ratio (SNR) improvement above 20 dB. Furthermore, this algorithm performs robustly, yields accurate echo estimation, and results in SNR enhancements ranging from 10 to 60 dB for composite signals having SNR as low as -10 dB.

Algorithms↗
PubMedDate not supplied

Diagnostic acceptability of FFT-based ECG data compression.

There are three signal domains in which ECG data compression can be performed, namely time domain, frequency domain and parameter extraction. The present paper deals with the frequency domain method of compression using fast Fourier transform. The algorithm has been tested on the third set of the CSE database library. A performance evaluation has been made using two important parameters, namely compression ratio and percent root-mean-square difference besides visual comparison. Further, in order to know the clinical acceptable quality of the reconstructed signal peak, boundary and interval measurements were made both on the reconstructed and the original signal of the same record for comparison. The visual examination reveals that most of the noise in the original signal had been filtered out during the compression. This amounts to reduction of electromyographic noise to a considerable extent. The experimental observations show that a compression ratio of 8 is feasible while ensuring clinical acceptability.

Algorithms↗
PubMed1985

A microcomputer program for comparison and alignment of DNA sequence gel readings.

During the course of determining the sequence of a large DNA fragment, it is necessary to cross-check numerous gel readings from different DNA fragments, in order to track and eliminate mistakes. An algorithm is presented that takes advantage of the high degree of homology between such sequences to construct an alignment of the matching regions. It does not require knowledge of a starting homology zone, neither large memory areas, even for sequences of several kilobases, and it can overcome large gaps or mismatch zones that correspond for instance to misinterpretation of compressions on sequence gels. This algorithm has been implemented in 6502 assembly language on an Apple II computer as an extension to the PEGASE sequence handling system.

Algorithms↗
PubMed2003

"Balanced" orbital decompression for severe Graves' orbitopathy: technique with treatment algorithm.

BACKGROUND: Graves' orbitopathy can produce proptosis, compressive optic neuropathy, and extraocular motility abnormalities; symptoms result from an increase in orbital volume due to expansion of intraorbital fat, with or without extraocular muscle involvement. STUDY DESIGN: We conducted a chart review of patients who underwent orbital decompression to treat Graves' orbitopathy. Twenty-two orbits (13 patients) underwent orbital bone decompression, of which 17 orbits (9 patients) underwent the combined medial and lateral "balanced" decompression. RESULTS: All patients had significant improvement with an average decrease in proptosis of 5.9 mm in the balanced decompression group. Restoration of normal optic nerve function was achieved in all patients with compressive optic neuropathy. Diplopia was noted in 4 patients (30.7%) preoperatively. Two patients had new postoperative diplopia (15.35%). CONCLUSION: In our experience, "balanced" decompression results in a reduction of proptosis and improved optic nerve function and has a low incidence of complications.

Adult↗
PubMed2006

Computer-aided detection of solid lung nodules in lossy compressed multidetector computed tomography chest exams.

RATIONALE AND OBJECTIVES: To assess the effect of three-dimensional (3D) lossy image compression of multidetector computed tomography chest scans on computer-aided detection (CAD) of solid lung nodules greater than 4 mm in size. MATERIALS AND METHODS: A total of 120 cases, acquired with 1.25-mm collimation, were collected from 5 different sites, of which 66/120 were low-dose cases. Two chest radiologists established that 37 cases had no actionable lung nodules; the remaining 83 cases contained 169 nodules (range 3.8-35.0 mm, mean 5.8 mm +/- 3.0 [SD]). All cases were compressed using the 3D Set Partitioning in Hierarchical Trees algorithm to 24:1, 48:1, and 96:1 levels. A study of the effect of compression on computer-aided detection (CAD) sensitivity was performed at operating points of 2.5 false marks (FM), 5 FM, and 10 FM per case using McNemar's test. Logistic regression models were used to evaluate the impact on CAD sensitivity by compression level on nodule and image characteristics. RESULTS: Compared with no compression, there was no significant degradation in CAD sensitivity found at any of the studied compression levels and operating points. However, between compression levels, there was marginal association with sensitivity. Specifically, 24:1 level was significantly better than 96:1 at all operating points, and occasionally better than no compression at 10 FM/case. Based on multivariate analysis, nodule location was found to be a significant predictor (P = .01) with a lower sensitivity associated with juxtapleural nodules. Nodule size, dose, reconstruction filter, and contrast medium were not significant predictors. CONCLUSION: CAD detection performance of solid lung nodules did not suffer until 48:1 compression.

Algorithms↗
PubMed2005

A compressed domain scheme for classifying block edge patterns.

Detecting and classifying edge components in images find a wide range of applications from perceptually improved coding schemes to content-based searches. In this paper, a fast and systematic scheme is proposed to classify the edge orientation of each block in discrete cosine transform (DCT)-compressed images. Derived from a simple, but acceptable, pixel-domain algorithm, the proposed scheme performs directly on DCT coefficient domain and, thus, saves the arithmetic operations by a considerable amount. The performance of the proposed method is validated by the experiments against various natural images.

Algorithms↗
PubMed1987

Back pain in the cancer patient: an algorithm for evaluation and management.

Epidural spinal cord compression is common in patients with metastatic cancer. Back pain is usually the first symptom and may be present for months before neurologic abnormalities occur. A favorable outcome depends on early diagnosis and treatment. For the management of this problem, we propose an algorithm that begins with the treatment of patients who need emergency care and proceeds with an orderly approach to the evaluation of less urgent cases. The central elements include the criteria for myelography and the rational use of corticosteroids, radiation therapy, and surgery.

Algorithms↗
PubMed2000

SMEM algorithm for mixture models.

We present a split-and-merge expectation-maximization (SMEM) algorithm to overcome the local maxima problem in parameter estimation of finite mixture models. In the case of mixture models, local maxima often involve having too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations, we repeatedly perform simultaneous split-and-merge operations using a new criterion for efficiently selecting the split-and-merge candidates. We apply the proposed algorithm to the training of gaussian mixtures and mixtures of factor analyzers using synthetic and real data and show the effectiveness of using the split-and-merge operations to improve the likelihood of both the training data and of held-out test data. We also show the practical usefulness of the proposed algorithm by applying it to image compression and pattern recognition problems.

Algorithms↗
PubMed1999

[Studies on data compression of 1-D NMR spectra using wavelet transform].

The multiresolution signal decomposition (MRSD) algorithm based on wavelet transform was applied to the compression of 1-D NMR spectra. A NMR spectrum which was composed of 32768 data points was investigated and the spectrum can be completely reconstructed with the residual square deviation (RSD) being as small as 2.7769 x 10(-4) when the spectrum was compressed to 512 data points. The relationship among the RSD and the different wavelet function, number of decomposiion and the compression ratio was also discussed.

English Abstract↗
PubMed2002

[An algorithm of a wavelet-based medical image quantization].

The compression of medical image is the key to study tele-medicine & PACS. We have studied the statistical distribution of wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is very much similar to that of Laplacian distribution. Based on the statistical properties of image wavelet decomposition, an image quantization algorithm is proposed. In this algorithm, we selected the sample-standard-deviation as the key quantization threshold in every wavelet subimage. The test has proved that, the main advantages of this algorithm are simple computing and the predictability of coefficients in different quantization threshold range. Also, high compression efficiency can be obtained. Therefore, this algorithm can be potentially used in tele-medicine and PACS.

Algorithms↗
PubMed1985

Is compression occurring in DRG prices?

Many analysts believe that the prices of truly high cost DRGs are set low relative to their actual costs whereas the prices of truly low cost DRGs are set high relative to their costs. To test whether such "compression" is occurring, I examined the algorithm that the Health Care Financing Administration used to create its DRG pricing structure. I then compared the HCFA algorithm with the more refined weighting systems used by Maryland and New Jersey to create their DRG payment systems. I found that compression is indeed occurring in the Medicare system relative to both the New Jersey and the Maryland systems. This compression will assume special urgency for some hospitals when the standardized national DRG payment system is phased in or if stringent limits are placed on the overall rate of increase in DRGs.

Centers for Medicare and Medicaid Services, U.S.↗
PubMed2005

Random close packing revisited: ways to pack frictionless disks.

We create collectively jammed (CJ) packings of 50-50 bidisperse mixtures of smooth disks in two dimensions (2D) using an algorithm in which we successively compress or expand soft particles and minimize the total energy at each step until the particles are just at contact. We focus on small systems in 2D and thus are able to find nearly all of the collectively jammed states at each system size. We decompose the probability P(phi) for obtaining a collectively jammed state at a particular packing fraction phi into two composite functions: (1) the density of CJ packing fractions rho(phi), which only depends on geometry, and (2) the frequency distribution beta(phi), which depends on the particular algorithm used to create them. We find that the function rho(phi) is sharply peaked and that beta(phi) depends exponentially on phi. We predict that in the infinite-system-size limit the behavior of P(phi) in these systems is controlled by the density of CJ packing fractions--not the frequency distribution. These results suggest that the location of the peak in P(phi) when N --> infinity can be used as a protocol-independent definition of random close packing.

Journal Article↗
PubMed2004

Automatic foveation for video compression using a neurobiological model of visual attention.

We evaluate the applicability of a biologically-motivated algorithm to select visually-salient regions of interest in video streams for multiply-foveated video compression. Regions are selected based on a nonlinear integration of low-level visual cues, mimicking processing in primate occipital, and posterior parietal cortex. A dynamic foveation filter then blurs every frame, increasingly with distance from salient locations. Sixty-three variants of the algorithm (varying number and shape of virtual foveas, maximum blur, and saliency competition) are evaluated against an outdoor video scene, using MPEG-1 and constant-quality MPEG-4 (DivX) encoding. Additional compression radios of 1.1 to 8.5 are achieved by foveation. Two variants of the algorithm are validated against eye fixations recorded from four to six human observers on a heterogeneous collection of 50 video clips (over 45 000 frames in total). Significantly higher overlap than expected by chance is found between human and algorithmic foveations. With both variants, foveated clips are, on average, approximately half the size of unfoveated clips, for both MPEG-1 and MPEG-4. These results suggest a general-purpose usefulness of the algorithm in improving compression ratios of unconstrained video.

Adult↗
PubMed2006

Improving diagnostic quality of MR images through controlled lossy compression using SPIHT.

This paper attempts to improve the diagnostic quality of magnetic resonance (MR) images through application of lossy compression as a noise-reducing filter. The amount of imaging noise present in MR images is compared with the amount of noise introduced by the compression, with particular attention given to the situation where the compression noise is a fraction of the imaging noise. A popular wavelet-based algorithm with good performance, Set Partitioning in Hierarchical Trees (SPIHT), was employed for the lossy compression. Tests were conducted with a number of MR patient images and corresponding phantom images. Different plausible ratios between imaging noise and compression noise (ICR) were considered, and the achievable compression gain through the controlled lossy compression was evaluated. Preliminary results show that at certain ICR's, it becomes virtually impossible to distinguish between the original and compressed-decompressed image. Radiologists presented with a blind test, in certain cases, showed preference to the compressed image rather than the original uncompressed ones, indicating that under controlled circumstances, lossy image compression can be used to improve the diagnostic quality of the MR images.

Algorithms↗
PubMed2004

Elimination of the friction effects in unconfined compression tests of biomaterials and soft tissues.

The mechanical properties of biomaterials and soft tissues are determined conventionally using unconfined compression tests. In such tests, frictionless specimen/platen contact in unconfined compression tests has to be assumed in determining the material properties of the materials. Previous theoretical analysis demonstrated, however, that the effects of the friction at the specimen/platen contact interface on the measured stress responses are non-negligible. In this study, a computational approach was proposed to eliminate the effects of friction. The friction coefficient between the specimen and the compression platens is measured first. Using a finite element model, the stress-strain relationship, without the influence of the friction effects, can be derived from the experimental data obtained in conventional unconfined compression tests. In order to validate the proposed approach, unconfined compressive tests of rubber have been performed.

Algorithms↗
PubMed2001

Modified lattice Boltzmann method for compressible fluid simulations.

A modified lattice Boltzmann algorithm is shown to have much better stability to growing temperature perturbations, when compared with the standard lattice Boltzmann algorithm. The damping rates of long-wavelength waves, which determine stability, are derived using a collisional equilibrium distribution function which has the property that the Euler equations are obtained exactly in the limit of zero time step. Using this equilibrium distribution function, we show that our algorithm has inherent positive hyperviscosity and hyperdiffusivity, for very small values of viscosity and thermal diffusivity, which are lacking in the standard algorithm. Short-wavelength modes are shown to be stable for temperatures greater than a lower limit. Results from a computer code are used to compare these algorithms, and to confirm the damping rate predictions made analytically. Finite amplitude sound waves in the simulated fluid steepen, as expected from gas dynamic theory.

Journal Article↗