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PubMed2006

Context-based coding of bilevel images enhanced by digital straight line analysis.

A new efficient compression scheme for bilevel images containing locally straight edges is presented. This paper is especially focused on lossless (intra) coding of binary shapes for image and video objects, but other images with similar characteristics such as line drawings, layers of digital maps, or segmentation maps are also encoded efficiently. The algorithm is not targeted at document images with text, which can be coded efficiently with dictionary-based techniques as in JBIG2. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding. Tested on individual images of standard TV resolution binary shapes and the binary layers of a digital map, the proposed algorithm outperforms PWC, JBIG, JBIG2, and MPEG-4 CAE. On the binary shapes, the code lengths are reduced by 21%, 27%, 28%, and 41%, respectively. On the map layers, the reductions are 31%, 34%, 32%, and 64%, respectively. The algorithm is also more efficient on the test material than the state-of-the-art generic bilevel image coder free tree.

Algorithms↗
PubMed2006

Nonlinear image representation for efficient perceptual coding.

Image compression systems commonly operate by transforming the input signal into a new representation whose elements are independently quantized. The success of such a system depends on two properties of the representation. First, the coding rate is minimized only if the elements of the representation are statistically independent. Second, the perceived coding distortion is minimized only if the errors in a reconstructed image arising from quantization of the different elements of the representation are perceptually independent. We argue that linear transforms cannot achieve either of these goals and propose, instead, an adaptive nonlinear image representation in which each coefficient of a linear transform is divided by a weighted sum of coefficient amplitudes in a generalized neighborhood. We then show that the divisive operation greatly reduces both the statistical and the perceptual redundancy amongst representation elements. We develop an efficient method of inverting this transformation, and we demonstrate through simulations that the dual reduction in dependency can greatly improve the visual quality of compressed images.

Algorithms↗
PubMed1998

Urodynamics and transurethral microwave thermotherapy.

In this paper the role and value of urodynamic measurements in symptomatic benign prostatic hyperplasia (BPH) patients selected for transurethral microwave thermotherapy (TUMT) reviewed. Although pressure-flow studies alone can diagnose benign prostatic obstruction, the level of acceptance of urodynamic investigations in BPH remains low, reportedly due to their cost and to their invasive and time-consuming nature. Furthermore, the observation that extremely different treatment modalities in BPH have nearly the same symptomatic outcome, independently of their influence on obstruction, has played a part in raising doubt as to the value of baseline urodynamics as a predictor of clinical success. Pre- and posttherapy urodynamic investigations in TUMT-treated patients have shown that urodynamic algorithms must be capable of distinguishing between compressive and constrictive types of obstruction to document the limited effects of low-energy TUMT on obstruction. Furthermore, it has been shown that urodynamics evaluated in this way seems to be the only predictor of the clinical success of TUMT when improvements in the objective parameters Qmax (peak uroflow) and residual urine are included in the definition of outcome.

Diathermy↗
PubMed2000

Isomer generation: semantic rules for detection of isomorphism

The problem of exhaustive generation of a nonredundant set of structural formulas (graphs) of acyclic alkanes was considered. A technique based on the compressed adjacency matrix (CAM) was proposed. The algorithm generates CAMs, which encode trees numbered according to the Morgan naming algorithm. Out of this set of CAMs those corresponding to the maximal Morgan codes--which in fact are the CAMs of canonically numbered isomers--must be found. CAMs are conceived as "sentences" of a primitive language. Sentences violating the syntactic and semantic rules of this language have to be discarded. In this paper three semantic rules have been proposed. The algorithm devised is efficient, and the decision to retain or to reject the actual structure does not involve any comparison with other structures. It was proved that several subsets of CAMs will not contain any maximal CAM and therefore it is not necessary to generate them. The whole procedure was illustrated by generating CAMs of all acyclic graphs containing nine vertices.

Journal Article↗
PubMed1997

Digital storage and analysis of color Doppler echocardiograms.

Color Doppler flow mapping has played an important role in clinical echocardiography. Most of the clinical work, however, has been primarily qualitative. Although qualitative information is very valuable, there is considerable quantitative information stored within the velocity map that has not been extensively exploited so far. Recently, many researchers have shown interest in using the encoded velocities to address the clinical problems such as quantification of valvular regurgitation, calculation of cardiac output, and characterization of ventricular filling. In this article, we review some basic physics and engineering aspects of color Doppler echocardiography, as well as drawbacks of trying to retrieve velocities from video tape data. Digital storage, which plays a critical role in performing quantitative analysis, is discussed in some detail with special attention to velocity encoding in DICOM 3.0 (medical image storage standard) and the use of digital compression. Lossy compression can considerably reduce file size with minimal loss of information (mostly redundant); this is critical for digital storage because of the enormous amount of data generated (a 10 minute study could require 18 Gigabytes of storage capacity). Lossy JPEG compression and its impact on quantitative analysis has been studied, showing that images compressed at 27:1 using the JPEG algorithm compares favorably with directly digitized video images, the current goldstandard. Some potential applications of these velocities in analyzing the proximal convergence zones, mitral inflow, and some areas of future development are also discussed in the article.

Algorithms↗
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↗
PubMed2003

Automatic learning of the morphology of medical language using information compression.

Conversion of free-text strings in a natural language to a standard representation (codes) is an important reoccurring problem in biomedical informatics. Determining the content of a string involves identifying its meaningful constituents (morphemes). One current method of identifying these constituents is to look them up in a preexisting table (lexicon). Manual construction of lexicons and grammars in complex domains such as biomedicine is extremely laborious. As an alternative to the lexico-grammatical approach, we introduce a segmentation algorithm that automatically learns lexical and structural preferences from corpora via information compression. The method is based on the Minimum Description Length (MDL) principle from classic information theory.

Algorithms↗
PubMed2004

Context modeling based on context quantization with application in wavelet image coding.

Context modeling is widely used in image coding to improve the compression performance. However, with no special treatment, the expected compression gain will be cancelled by the model cost introduced by high order context models. Context quantization is an efficient method to deal with this problem. In this paper, we analyze the general context quantization problem in detail and show that context quantization is similar to a common vector quantization problem. If a suitable distortion measure is defined, the optimal context quantizer can be designed by a Lloyd style iterative algorithm. This context quantization strategy is applied to an embedded wavelet coding scheme in which the significance map symbols and sign symbols are directly coded by arithmetic coding with context models designed by the proposed quantization algorithm. Good coding performance is achieved.

Algorithms↗
PubMed2005

Using sequence compression to speedup probabilistic profile matching.

MOTIVATION: Matching a biological sequence against a probabilistic pattern (or profile) is a common task in computational biology. A probabilistic profile, represented as a scoring matrix, is more suitable than a deterministic pattern to retain the peculiarities of a given segment of a family of biological sequences. Brute-force algorithms take O(NP) to match a sequence of N characters against a profile of length P << N. RESULTS: In this work, we exploit string compression techniques to speedup brute-force profile matching. We present two algorithms, based on run-length and LZ78 encodings, that reduce computational complexity by the compression factor of the encoding.

Algorithms↗
PubMed1998

An energy dissipation-based model for damage stimulated bone adaptation.

Based on experimental observations, several researchers have proposed a role for damage processes in stimulating an adaptive response in bone. In the current study we propose a model for bone adaptation based on cyclic energy dissipation as a measure of bone damage creation. By reanalyzing the fatigue data of Pattin et al. (1996), we derive a uniaxial form of the damage based formulation applicable to cortical regions experiencing primarily longitudinal stresses. Because of the experimentally observed difference between damage formation under tension and compression (Pattin et al., 1996), this formulation naturally predicts a difference in the adaptive response to tensile and compressive loading. This feature distinguishes the new formulation from existing strain energy based adaptation theories which treat tensile and compressive strains identically. Thus, developmental adaptation in response to unequal generation of damage provides one possible explanation for the experimentally observed difference between peak tensile and compressive bone surface strains.

Adaptation, Physiological↗
PubMed2004

Super-resolution reconstruction of compressed video using transform-domain statistics.

Considerable attention has been directed to the problem of producing high-resolution video and still images from multiple low-resolution images. This multiframe reconstruction, also known as super-resolution reconstruction, is beginning to be applied to compressed video. Super-resolution techniques that have been designed for raw (i.e., uncompressed) video may not be effective when applied to compressed video because they do not incorporate the compression process into their models. The compression process introduces quantization error, which is the dominant source of error in some cases. In this paper, we propose a stochastic framework where quantization information as well as other statistical information about additive noise and image prior can be utilized effectively.

Algorithms↗
PubMedDate not supplied

Constitutive modelling of brain tissue: experiment and theory.

Recent developments in computer-integrated and robot-aided surgery--in particular, the emergence of automatic surgical tools and robots--as well as advances in virtual reality techniques, call for closer examination of the mechanical properties of very soft tissues (such as brain, liver, kidney, etc.). The ultimate goal of our research into the biomechanics of these tissues is the development of corresponding, realistic mathematical models. This paper contains experimental results of in vitro, uniaxial, unconfined compression of swine brain tissue and discusses a single-phase, non-linear, viscoelastic tissue model. The experimental results obtained for three loading velocities, ranging over five orders of magnitude, are presented. The applied strain rates have been much lower than those applied in previous studies, focused on injury modelling. The stress-strain curves are concave upward for all compression rates containing no linear portion from which a meaningful elastic modulus might be determined. The tissue response stiffened as the loading speed increased, indicating a strong stress-strain rate dependence. The use of the single-phase model is recommended for applications in registration, surgical operation planning and training systems as well as a control system of an image-guided surgical robot. The material constants for the brain tissue are evaluated. Agreement between the proposed theoretical model and experiment is good for compression levels reaching 30% and for loading velocities varying over five orders of magnitude.

Algorithms↗
PubMed2006

An efficient content-adaptive motion-compensated 3-D DWT with enhanced spatial and temporal scalability.

We propose a novel, content adaptive method for motion-compensated three-dimensional wavelet transformation (MC 3-D DWT) of video. The proposed method overcomes problems of ghosting and nonaligned aliasing artifacts which can arise in regions of motion model failure, when the video is reconstructed at reduced temporal or spatial resolutions. Previous MC 3-D DWT structures either take the form of MC temporal DWT followed by a spatial transform ("t+2D"), or perform the spatial transform first ("2D + t"), limiting the spatial frequencies which can be jointly compensated in the temporal transform, and hence limiting the compression efficiency. When the motion model fails, the "t + 2D" structure causes nonaligned aliasing artifacts in reduced spatial resolution sequences. Essentially, the proposed transform continuously adapts itself between the "t + 2D" and "2D + t" structures, based on information available within the compressed bit stream. Ghosting artifacts may also appear in reduced frame-rate sequences due to temporal low-pass filtering along invalid motion trajectories. To avoid the ghosting artifacts, we continuously select between different low-pass temporal filters, based on the estimated accuracy of the motion model. Experimental results indicate that the proposed adaptive transform preserves high compression efficiency while substantially improving the quality of reduced spatial and temporal resolution sequences.

Algorithms↗
PubMedDate not supplied

Adaptive extraction of time-varying isosurfaces.

We present an algorithm for adaptively extracting and rendering isosurfaces from compressed time-varying volume data sets. Tetrahedral meshes defined by longest edge bisection are used to create a multiresolution representation of the volume in the spatial domain that is adapted over time to approximate the time-varying volume. The reextraction of the isosurface at each time step is accelerated with the vertex programming capabilities of modern graphics hardware. A data layout scheme which follows the access pattern indicated by mesh refinement is used to access the volume in a spatially and temporally coherent manner. This data layout scheme allows our algorithm to be used for out-of-core visualization.

Journal Article↗
PubMed2001

Black copper phosphate cement: does it have a future?

The aim of this study was to compare the in vitro compressive strength and solubility of a black copper cement with one established restorative material (a conventional glass ionomer cement) and two temporary restorative materials (a zinc phosphate and a zinc polycarboxylate cement). The mean compressive strength of black copper cement varied with the powder: liquid ratio, with an intermediate ratio having a comparable strength to that of the zinc polycarboxylate cement (the best material in this respect). The solubility of the black copper cement at all mixing ratios was significantly greater than that of all other test materials.

Algorithms↗
PubMed2006

Use of Fresnelets for phase-shifting digital hologram compression.

Fresnelets are wavelet-like base functions specially tailored for digital holography applications. We introduce their use in phase-shifting interferometry (PSI) digital holography for the compression of such holographic data. Two compression methods are investigated. One uses uniform quantization of the Fresnelet coefficients followed by lossless coding, and the other uses set portioning in hierarchical trees (SPIHT) coding. Quantization and lossless coding of the original data is used to compare the performance of the proposed algorithms. The comparison reveals that the Fresnelet transform of phase-shifting holograms in combination with SPIHT or uniform quantization can be used very effectively for the compression of holographic data. The performance of the new compression schemes is demonstrated on real PSI digital holographic data.

Algorithms↗
PubMed1999

Data compression methods for EEG.

Modem brain research experiments require the recording of large amounts of high-accuracy EEG data. Sampling frequency, bit resolution and number of channels are significantly larger than in routine clinical measurements. Because of this, the need of efficient signal compression has emerged. This paper presents a survey of available methods and explores some techniques, both lossy and lossless, for compressing EEG signals.

Algorithms↗
PubMed2005

Medical image compression using 3-D Hartley transform.

In this paper, 3-D discrete Hartley transform is applied for the compression of two medical modalities, namely, magnetic resonance images and X-ray angiograms and the performance results are compared with those of 3-D discrete cosine and Fourier transforms using the parameters such as PSNR and bit rate. It is shown that the 3-D discrete Hartley transform is better than the other two transforms for magnetic resonance brain images whereas for the X-ray angiograms, the 3-D discrete cosine transform is found to be superior.

Algorithms↗