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At least 793 records · Page 44Linked to original sources
PubMed2004

Design of signal-adapted multidimensional lifting scheme for lossy coding.

This paper proposes a new method for the design of lifting filters to compute a multidimensional nonseparable wavelet transform. Our approach is stated in the general case, and is illustrated for the 2-D separable and for the quincunx images. Results are shown for the JPEG2000 database and for satellite images acquired on a quincunx sampling grid. The design of efficient quincunx filters is a difficult challenge which has already been addressed for specific cases. Our approach enables the design of less expensive filters adapted to the signal statistics to enhance the compression efficiency in a more general case. It is based on a two-step lifting scheme and joins the lifting theory with Wiener's optimization. The prediction step is designed in order to minimize the variance of the signal, and the update step is designed in order to minimize a reconstruction error. Application for lossy compression shows the performances of the method.

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↗
PubMed2005

Motion compensated lossy-to-lossless compression of 4-D medical images using integer wavelet transforms.

This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.

Algorithms↗
PubMed2006

Perceptually lossless medical image coding.

A novel perceptually lossless coder is presented for the compression of medical images. Built on the JPEG 2000 coding framework, the heart of the proposed coder is a visual pruning function, embedded with an advanced human vision model to identify and to remove visually insignificant/irrelevant information. The proposed coder offers the advantages of simplicity and modularity with bit-stream compliance. Current results have shown superior compression ratio gains over that of its information lossless counterparts without any visible distortion. In addition, a case study consisting of 31 medical experts has shown that no perceivable difference of statistical significance exists between the original images and the images compressed by the proposed coder.

Algorithms↗
PubMed2003

Ultrasonic tissue characterization for prostate diagnostics: spectral parameters vs. texture parameters.

An ultrasonic multi-feature tissue characterizing system for the detection of prostate cancer is presented. The system is based on the processing of radio frequency (RF) ultrasonic echo data. Data from 100 patients was acquired in a clinical study. Parameters are extracted from the RF echo data and classified using two adaptive network-based fuzzy inference systems (FIS) working in parallel as a nonlinear classifier. Next to spectral parameters, conventional texture parameters are calculated using demodulated and log-compressed echo data. In the first approach, the classifier is trained on both, spectral and texture parameters. In the second approach, the classifier is only trained on texture parameters. Classification results of both approaches are compared and it is demonstrated, that only the use of spectral parameters yields satisfying classification results. Results of a minimum distance classifier (MDC) are presented for comparison with the fuzzy inference system. For the final fuzzy inference systems used in this approach, the area under the ROC curve is between 84% and 86% for the combined approach and between 70% and 74% for the approach based on texture parameters only.

Aged↗
PubMed2003

Lossy compression of eye movement and auditory brainstem response signals.

Eye movement and auditory brainstem response signals recorded for balance and hearing investigations were used as a medical test battery for several types of lossy compression techniques. These signals are associated with the function of the ears. The former signals are used to assess the balance problems (especially vertigo) of a subject and the latter his or her hearing problems. New technique is also presented based on successive approximation quantization. The effect of information loss on medical parameters computed from the signals in the course of compression was evaluated for brainstem response signals. It is important to ensure that lossy compression techniques of these biomedical signals do not impair medical parameter values computed from the signals.

Algorithms↗
PubMed2006

An effective and efficient compression algorithm for ECG signals with irregular periods.

This paper presents an effective and efficient preprocessing algorithm for two-dimensional (2-D) electrocardiogram (ECG) compression to better compress irregular ECG signals by exploiting their inter- and intra-beat correlations. To better reveal the correlation structure, we first convert the ECG signal into a proper 2-D representation, or image. This involves a few steps including QRS detection and alignment, period sorting, and length equalization. The resulting 2-D ECG representation is then ready to be compressed by an appropriate image compression algorithm. We choose the state-of-the-art JPEG2000 for its high efficiency and flexibility. In this way, the proposed algorithm is shown to outperform some existing arts in the literature by simultaneously achieving high compression ratio (CR), low percent root mean squared difference (PRD), low maximum error (MaxErr), and low standard derivation of errors (StdErr). In particular, because the proposed period sorting method rearranges the detected heartbeats into a smoother image that is easier to compress, this algorithm is insensitive to irregular ECG periods. Thus either the irregular ECG signals or the QRS false-detection cases can be better compressed. This is a significant improvement over existing 2-D ECG compression methods. Moreover, this algorithm is not tied exclusively to JPEG2000. It can also be combined with other 2-D preprocessing methods or appropriate codecs to enhance the compression performance in irregular ECG cases.

Algorithms↗
PubMed2025

Logan: Planetary-Scale Genome Assembly Surveys Life's Diversity.

The breadth of life's diversity is unfathomable, but public nucleic acid sequencing data offers a window into the dispersion and evolution of genetic diversity across Earth. However the rapid growth and accumulation of sequence data have outpaced efficient analysis capabilities. The largest collection of freely available sequencing data is the Sequence Read Archive (SRA), comprising 27.3 million datasets or 5 × 1016 basepairs. To realize the potential of the SRA, we constructed Logan, a massive sequence assembly transforming short reads into long contigs and compressing the data over 100-fold, enabling highly efficient petabase-scale analysis. We created Logan-Search, a k-mer index of Logan for free planetary-scale sequence search, returning matches in minutes. We used Logan contigs to identify >200 million plastic-degrading enzyme homologs, and validate novel enzymes with catalytic activities exceeding current reference standards. Further, we vastly expand the known diversity of proteins (30-fold over UniRef50), plasmids (22-fold over PLSDB), P4 satellites (4.5-fold), and the recently described Obelisk RNA elements (3.7-fold). Logan also enables ecological and biomedical data mining, such as global tracking of antimicrobial resistance genes and the characterization of viral reactivation across millions of human BioSamples. By transforming the SRA, Logan democratizes access to the world's public genetic data and opens frontiers in biotechnology, molecular ecology, and global health.

Journal Article↗
PubMed2003

A genetic segmentation of ECG signals.

This paper is concerned with a development of a segmentation technique for electrocardiogram (ECG) signals. Such segmentation is aimed at a lossy signal compression in which each segment can be captured by a simple geometric construct such as, e.g., a linear or quadratic function. The crux of the proposed construct lies in the determination of the optimal segments of data over which they exhibit the highest possible monotonicity (or lowest variability) of the ECG signal. In this sense, the proposed approach generalizes a fundamental and commonly encountered problem of function (data) linearization. The segments are genetically developed using a standard technique of genetic algorithms (GAs). The two fundamental GA constructs, namely a topology of a chromosome and a fitness function governing the optimization process are discussed in detail. The chromosome being coded as a series of floating point numbers contains the endpoints of the segments (segmentation points). The fitness function to be maximized quantifies a level of monotonicity of the ECG data encountered within the segments and takes into consideration differences between the extreme values (minimum and maximum) of its derivatives. As a result of the genetic optimization, we build segments of ECG signals encompassing monotonic (increasing or decreasing) regions of the signal exhibiting a minimal level of variability. A series of experiments dealing with several classes of ECG signals (namely, normal, left bundle branch block beat, and right bundle branch block beat) visualize the effectiveness of the approach and shows the specificity of the linear segments of data. Furthermore, we elaborate on the relationship between the values of the fitness function and the approximation capabilities (quantified by a sum of squared errors between the local model and the data) of the segments of the signal and show that these two descriptors are highly related.

Algorithms↗
PubMed2004

Embedded image compression based on wavelet pixel classification and sorting.

The method of modeling and ordering in wavelet domain is very important to design a successful algorithm of embedded image compression. In this paper, the modeling is limited to "pixel classification," the relationship between wavelet pixels in significance coding. Similarly, the ordering is limited to "pixel sorting," the coding order of wavelet pixels. We use pixel classification and sorting to provide a better understanding of previous works. The image pixels in wavelet domain are classified and sorted, either explicitly or implicitly, for embedded image compression. A new embedded image code is proposed based on a novel pixel classification and sorting (PCAS) scheme in wavelet domain. In PCAS, pixels to be coded are classified into several quantized contexts based on a large context template and sorted based on their estimated significance probabilities. The purpose of pixel classification is to exploit the intraband correlation in wavelet domain. Pixel sorting employs several fractional bit-plane coding passes to improve the rate-distortion performance. The proposed pixel classification and sorting technique is simple, yet effective, producing an embedded image code with excellent compression performance. In addition, our algorithm is able to provide either spatial or quality scalability with flexible complexity.

Algorithms↗
PubMed2006

Wavelet-based medical image compression with adaptive prediction.

A lossless wavelet-based image compression method with adaptive prediction is proposed. Firstly, we analyze the correlations between wavelet coefficients to identify a proper wavelet basis function, then predictor variables are statistically test to determine which relative wavelet coefficients should be included in the prediction model. At last, prediction differences are encoded by an adaptive arithmetic encoder. Instead of relying on a fixed number of predictors on fixed locations, we proposed the adaptive prediction approach to overcome the multicollinearity problem. The proposed innovative approach integrating correlation analysis for selecting wavelet basis function with predictor variable selection is fully achieving high accuracy of prediction. Experimental results show that the proposed approach indeed achieves a higher compression rate on CT, MRI and ultrasound images comparing with several state-of-the-art methods.

Data Compression↗
PubMed2004

Design of vector quantizer for image compression using self-organizing feature map and surface fitting.

We propose a new scheme of designing a vector quantizer for image compression. First, a set of codevectors is generated using the self-organizing feature map algorithm. Then, the set of blocks associated with each code vector is modeled by a cubic surface for better perceptual fidelity of the reconstructed images. Mean-removed vectors from a set of training images is used for the construction of a generic codebook. Further, Huffman coding of the indices generated by the encoder and the difference-coded mean values of the blocks are used to achieve better compression ratio. We proposed two indices for quantitative assessment of the psychovisual quality (blocking effect) of the reconstructed image. Our experiments on several training and test images demonstrate that the proposed scheme can produce reconstructed images of good quality while achieving compression at low bit rates. Index Terms-Cubic surface fitting, generic codebook, image compression, self-organizing feature map, vector quantization.

Algorithms↗
PubMed2006

Semi-regular representation and progressive compression of 3-D dynamic mesh sequences.

We propose an algorithm that represents three-dimensional dynamic objects with a semi-regular mesh sequence and compresses the sequence using the spatiotemporal wavelet transform. Given an irregular mesh sequence, we construct a semi-regular mesh structure for the first frame and then map it to subsequent frames based on the hierarchical motion estimation. The regular structure of the resulting mesh sequence facilitates the application of advanced coding schemes and other signal processing techniques. To encode the mesh sequence compactly, we develop an embedded coding scheme, which supports signal-to-noise ratio and temporal scalability modes. Simulation results demonstrate that the proposed algorithm provides significantly better compression performance than the static mesh coder, which encodes each frame independently.

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

Effects of lossy image compression on quantitative image analysis of cell nuclei.

OBJECTIVE: To investigate whether statistically significant changes occur in quantitative image analysis of cell nuclei when lossy image compression techniques are used. STUDY DESIGN: Thirty-five stoichiometric, Feulgen-stained samples of rat hepatocytes, human thyroid and ovarian cancer cell nuclei were used. Image analysis was performed by a computerized system that used AutoCyte LINK V1.1.1.56 software (Burlington, North Carolina, U.S.A.) for image acquisition and Zeiss Vision KS 400 V3.0 software (Oberkochen, Germany) for quantitative image analysis. After lossy JPEG compression of acquired images at different quality levels, some densitometric features were selected and measurements performed. RESULTS: We observed that nearly all the standard densitometric features showed statistically significant changes when images were compressed with the lossy JPEG algorithm. However, most invariant densitometric moment features remained free of statistically significant changes. CONCLUSION: The standard densitometric measurements that we used do not tolerate lossy compression. However, analyses using invariant densitometric features may be performed on images compressed with lossy JPEG, resulting in simpler, less expensive systems demanding less network bandwidth.

Animals↗
PubMed2003

A block coding method that leads to significantly lower entropy values for the proteins and coding sections of Haemophilus influenzae.

A simple statistical block code in combination with the LZW-based compression utilities gzip and compress has been found to increase by a significant amount the level of compression possible for the proteins encoded in Haemophilus influenzae, the first fully sequenced genome. The method yields an entropy value of 3.665 bits per symbol (bps), which is 0.657 bps below the maximum of 4.322 bps and an improvement of 0.452 bps over the best known to date of 4.118 bps using Matsumoto, Sadakane, and Imai's lza-CTW algorithm. Calculations based on a compact inverse genetic code show that the genome has a maximum entropy of 1.757 bps for the coding regions, with a possibly lower actual entropy. These results hint at the existence of hitherto unexplored redundancies that do not show up in Markov models and are indicative of more internal structure than suspected in both the protein and the genome.

Algorithms↗
PubMed2006

Texture characterization for joint compression and classification based on human perception in the wavelet domain.

Today's multimedia applications demand sophisticated compression and classification techniques in order to store, transmit, and retrieve audio-visual information efficiently. Over the last decade, perceptually based image compression methods have been gaining importance. These methods take into account the abilities (and the limitations) of human visual perception (HVP) when performing compression. The upcoming MPEG 7 standard also addresses the need for succinct classification and indexing of visual content for efficient retrieval. However, there has been no research that has attempted to exploit the characteristics of the human visual system to perform both compression and classification jointly. One area of HVP that has unexplored potential for joint compression and classification is spatial frequency perception. Spatial frequency content that is perceived by humans can be characterized in terms of three parameters, which are: 1) magnitude; 2) phase; and 3) orientation. While the magnitude of spatial frequency content has been exploited in several existing image compression techniques, the novel contribution of this paper is its focus on the use of phase coherence for joint compression and classification in the wavelet domain. Specifically, this paper describes a human visual system-based method for measuring the degree to which an image contains coherent (perceptible) phase information, and then exploits that information to provide joint compression and classification. Simulation results that demonstrate the efficiency of this method are presented.

Algorithms↗
PubMed1998

Myoelectric activity of the ileum, cecum, and right ventral colon, and cecal emptying of radiolabeled markers in clinically normal ponies.

OBJECTIVES: To determine normal cecal emptying curves for liquid- and solid-phase radiolabeled markers and to further define myoelectric patterns of the ileum, cecum, and colon in healthy ponies. ANIMALS: 6 adult ponies. PROCEDURE: A cecal cannula and 12 bipolar Ag-AgCl recording electrodes were sutured to the ileum, cecum, and right ventral colon of the ponies. Radioisotopes, indium 111-labeled diethyltriaminepentaacetic acid (111In-DTPA) and technetium 99m (99mTc)-labeled sulfur colloid bound to egg albumen, were introduced through the cannula directly into the cecal body. Movement of these markers from the cecum was monitored by a gamma camera, and power exponential clearance curves were generated. Myoelectric data were collected before and after i.v. administration of isotonic saline (0.9% NaCl) solution, and were analyzed for spike burst (SB) rate, relative activity index, and mean burst duration. Myoelectric complexes were identified from observation of chart recordings or compressed, digitized data. RESULTS: Clearance curves were generated for liquid (111In-DTPA)- and solid (99mTc)-phase markers. Marker types were not different with respect to lag phase, but liquid markers emptied at a slightly faster rate than did solids. Baseline values were calculated after saline solution administration for each of the myoelectric variables investigated. A relation between ileal, cecal, and colonic myoelectric activity was identified. Activity consistent with the previously described colonic migrating myoelectric complex in the pelvic flexure was identified in the right ventral colon. CONCLUSIONS AND CLINICAL RELEVANCE: Baseline data on normal cecal emptying was obtained; this technique could be used to evaluate the effect of postulated motility-modifying treatments used in equine practice.

Animals↗