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PubMed2002

Astronomy. Laser telemetry from space.

Space missions currently on the drawing boards are expected to gather data at rates exceeding the transmission capabilities of today's telemetry systems by many orders of magnitude. Even on current missions, onboard data compression techniques are being implemented to compensate for lack of transmission speed. But while data compression can minimize the loss of data, it is no substitute for transmitting all of the data through a faster communications link. The transmission problem will soon reach crisis proportions and will affect astronomical, Earth resources, geophysical, meteorological, planetary and other space science missions. To overcome this communications bottleneck, the authors advocate the implementation of telemetry systems based on near-infrared laser transmission techniques. The fiber-optics communications industry has developed most of the basic components required for signal transmission in this wavelength band, which should make such a system affordable on scales relevant to the cost of anticipated space science missions.

Journal Article↗
PubMed1999

Best parameters selection for wavelet packet-based compression of magnetic resonance images.

Transmission of compressed medical images is becoming a vital tool in telemedicine. Thus new methods are needed for efficient image compression. This study discovers the best design parameters for a data compression scheme applied to digital magnetic resonance (MR) images. The proposed technique aims at reducing the transmission cost while preserving the diagnostic information. By selecting the wavelet packet's filters, decomposition level, and subbands that are better adapted to the frequency characteristics of the image, one may achieve better image representation in the sense of lower entropy or minimal distortion. Experimental results show that the selection of the best parameters has a dramatic effect on the data compression rate of MR images. In all cases, decomposition at three or four levels with the Coiflet 5 wavelet (Coif 5) results in better compression performance than the other wavelets. Image resolution is found to have a remarkable effect on the compression rate.

Brain↗
PubMed2005

Wavelet compression of three-dimensional time-lapse biological image data.

The use of multifocal-plane, time-lapse recordings of living specimens has allowed investigators to visualize dynamic events both within ensembles of cells and individual cells. Recordings of such four-dimensional (4D) data from digital optical sectioning microscopy produce very large data sets. We describe a wavelet-based data compression algorithm that capitalizes on the inherent redunancies within multidimensional data to achieve higher compression levels than can be obtained from single images. The algorithm will permit remote users to roam through large 4D data sets using communication channels of modest bandwidth at high speed. This will allow animation to be used as a powerful aid to visualizing dynamic changes in three-dimensional structures.

Algorithms↗
PubMed1990

Vector quantization for compression of multichannel ECG.

We propose a scheme based on vector quantization (VQ) for the data-compression of multichannel ECG waveforms. N-channel ECG is first coded using m-AZTEC, a new, multichannel extension of the AZTEC algorithm. As in AZTEC, the waveform is approximated using only lines and slopes; however, in m-AZTEC, the N-channels are coded simultaneously into a sequence of N + 1 dimensional vectors, thus exploiting the correlation that exists across channels in the AZTEC duration-parameter. Classified vector quantization (CVQ) of the m-AZTEC output is next performed to exploit the correlation in the other AZTEC parameter, namely, the value-parameter. CVQ preserves the waveform morphology by treating the lines and slopes as two perceptually-distinct classes. Both m-AZTEC and CVQ provide data-compression and their performance improves as the number of channels increases. Moreover, the final output differs little from the AZTEC output and hence ought to enjoy the same acceptability.

Algorithms↗
PubMed1996

Non-linear algorithms for processing biological signals.

This paper illustrates different approaches to the analysis of biological signals based on non-linear methods. The performance of such approaches, despite the greater methodological and computational complexity is, in many instances, more successful compared to linear approaches, in enhancing important parameters for both physiological studies and clinical protocols. The methods introduced employ median filters for pattern recognition, adaptive segmentation, data compression, prediction and data modelling as well as multivariate estimators in data clustering through median learning vector quantizers. Another approach described uses Wiener-Volterra kernel technique to obtain a satisfactory estimation and causality test among EEG recordings. Finally, methods for the assessment of non-linear dynamic behaviour are discussed and applied to the analysis of heart rate variability signal. In this way invariant parameters are studied which describe non-linear phenomena in the modelling of the physiological systems under investigation.

Algorithms↗
PubMed1992

Image archival technologies.

A typical radiology department can create many gigabytes of image data per day and as much as 1 terabyte of data per year. Archiving and accessing this much data are substantial problems. One solution is data compression, which decreases data storage requirements and increases the rate of data transfer; however, standards are not yet available. Other solutions involve improvements in archival media. Jukebox subsystems allow automated access to multiple units. Digital magnetic tape, the standard medium, can store large amounts of information and enables easy updates or replacements; more practical technologies have been introduced in recent years. Digital videotape allows storage of digital video data and features a high rate of data transfer. Optical disks, now the preferred permanent archival medium, have a large storage capacity and provide excellent long-term stability. Optical tape is also being investigated as a solution to the archiving dilemma. Which technology to choose depends on many factors, including needs of the institution and the cost, stability, transfer time, and storage capacity of the system.

Computer Storage Devices↗
PubMed2004

Morse description and geometric encoding of digital elevation maps.

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum error in the decoded elevation map, a property that is necessary for the majority of applications dealing with DEMs. We present the underlying theory and compression results for standard DEM data.

Algorithms↗
PubMed2004

Optimal context quantization in lossless compression of image data sequences.

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context Ct = (Xt-t1,Xt-t2,...,X t-tK) of a source symbol Xt into one of a set of conditioning states. The optimality of context quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet a random variable can be decomposed into a sequence of binary decisions, each of which is coded using optimal context quantization designed for the corresponding binary random variable. This optimized coding scheme is applied to digital maps and alpha-plane sequences. The proposed optimal context quantization technique can also be used to establish a lower bound on the achievable code length, and hence is a useful tool to evaluate the performance of existing heuristic context quantizers.

Algorithms↗
PubMed2005

Texture analysis in digitally-acquired echocardiographic images: the effect of JPEG compression and video storage.

The analysis of texture in video-stored echocardiographic images is an established method to characterize myocardial pathologies. We investigated whether or not texture parameters calculated from video-stored images and those derived from the joint photographic expert group (JPEG) format compressed data are equivalent to those calculated from uncompressed digital images. Texture parameters were calculated using uncompressed digital data, images stored on videotape, and three forms of compressed digital data (baseline JPEG, JPEG 2000 and lossless JPEG 2000). Video storage heavily affected most texture parameters. Although first-order texture parameters derived from JPEG-compressed images were generally equivalent to those derived from the uncompressed data, several second-order parameters differed significantly. We conclude that texture of video-stored images is not comparable to that of digitally-stored images and that JPEG compression changes important second-order texture parameters. This observation should be taken into account when analyzing texture of modern image data (uncompressed or compressed) and comparing the results with earlier studies utilizing video-stored data.

Data Compression↗
PubMed2006

A gzip-based algorithm to identify bacterial families by 16S rRNA.

AIMS: Microbial family identification of 16S rDNA sequences by applying a strategy based on algorithms for data compression. METHODS AND RESULTS: Perl scripts were developed to analyse similarities in microbial sequences, based on a gzip data compression technique. For each bacterial family (n=196) a 16S rRNA reference file was constructed to compare new queries looking at compression performance. An online user-friendly bioinformatics tool was built up to attribute a bacterial family to a 16S rRNA sequence. It was successfully applied to recognize different bacterial families, including Legionellaceae, Bacillaceae, Enterobacteriaceae, Acetobacteriaceae and Rhizobiaceae. The percentage of positive identifications is higher than 95% for fragments over 450 bp. CONCLUSIONS: A new bioinformatics approach has been developed to assign a taxonomic classification to a 16SrDNA sequence. An online tool provides quick and easy sequence attribution. The general principle can be applied to other genes of taxonomic interest. SIGNIFICANCE AND IMPACT OF THE STUDY: Availability of simple bioinformatics tools can support the development of molecular-based analysis and classification of bacteria, especially for environmental or uncultured strains.

Algorithms↗
PubMed2006

Mining, compressing and classifying with extensible motifs.

BACKGROUND: Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in the design of data compression schemes. Informally, a motif is a string of intermittently solid and wild characters that recurs more or less frequently in an input sequence or family of sequences. Motif discovery techniques and tools tend to be computationally imposing, however, special classes of "rigid" motifs have been identified of which the discovery is affordable in low polynomial time. RESULTS: In the present work, "extensible" motifs are considered such that each sequence of gaps comes endowed with some elasticity, whereby the same pattern may be stretched to fit segments of the source that match all the solid characters but are otherwise of different lengths. A few applications of this notion are then described. In applications of data compression by textual substitution, extensible motifs are seen to bring savings on the size of the codebook, and hence to improve compression. In germane contexts, in which compressibility is used in its dual role as a basis for structural inference and classification, extensible motifs are seen to support unsupervised classification and phylogeny reconstruction. CONCLUSION: Off-line compression based on extensible motifs can be used advantageously to compress and classify biological sequences.

Journal Article↗
PubMed2002

Computed tomography diagnosis utilizing compressed image data: an ROC analysis using acute appendicitis as a model.

Using receiver-operating characteristic (ROC) methodology, the ability to diagnose acute appendicitis with computed tomography (CT) images displayed at varying levels of lossy compression was evaluated. Nine sequential images over the ileocecal region were obtained from 53 consecutive patients with right lower quadrant pain who were clinically suspected to have acute appendicitis. Thirty were proven surgically to have acute appendicitis, alternative diagnoses confirmed in 23. The image sets were subjected to a lossy wavelet-based compression algorithm "Embedded Predictive Wavelet Image Coder" (EPWIC). Compression levels were: none, 8:1, 16:1, and 24:1, resulting in 4 sets of images per patient. Image sets were randomized and evaluated separately by 4 body radiologists on a 1,024 x 768-pixel SVGA color PC monitor in 512 x 512 format. The readers were aware of the clinical suspicion of appendicitis but were unaware of the positive fraction of cases. Individual and combined reader ROC and c2 analyses of sensitivity, specificity, and accuracy were determined. For all readers, sensitivity decreases at 16:1 and 24:1 levels (P <0.01, P <0.001, respectively). Accuracy decreased at 24:1 levels (P <0.01). Specificity was unaffected. By ROC analysis there was statistically significantly decreased area under the curve at 24:1 levels (P <0.02) as compared with uncompressed images. Finite levels of lossy wavelet compression may be applied to CT images without compromising diagnostic performance.

Acute Disease↗
PubMed1998

Towards multi-patient leadless and wireless cardiotocography via RF telemetry.

During labour the condition of the fetus is monitored by a cardiotocograph which displays fetal heart rate and a measure of uterine contractions. Ultrasound and tocodynamometer transducers are placed on the mother's abdomen and connected to a bedside monitor and display unit via a cable. This paper describes a prototype wireless system aimed at demonstrating the potential elimination of the cable which is undesirable in a number of respects. The radio link utilised operates at a frequency of 418 MHz with data compression and time division multiplexing (TDM) employed to allow up to 10 units to operate simultaneously on the same frequency in the same area. Data compression is achieved by extracting the Doppler ultrasound signal envelope and representing the frequency content of the signal using a zero crossing counting technique. Two Medium Access Control (MAC) protocols were considered, with a synchronised time division multiplexing system shown to offer greater throughput and resistance to interference than Carrier Sense Multiple Access (CSMA). This wireless RF telemetry system could be readily adapted for other multi-patient monitoring applications.

Cardiotocography↗
PubMed2006

Image reconstruction only by phase data in phase-shifting digital holography.

We describe data compression in phase-shifting digital holography. We demonstrate by experimentation that an image of a diffusely reflecting object can be reconstructed only by phase data of the derived complex amplitude. It is shown that reduction of the bit depth of the phase data does not seriously damage the image even down to 1 bit. We observe enhancement of halo in the image with low bit depths. This tendency is verified quantitatively by a one-dimensional simulation. Our procedure for smoothing the images that result from the data-compression methods is shown to be effective.

Journal Article↗
PubMed1986

Compressibility-structure relationship of globular proteins.

The adiabatic compressibility, -beta s, of 11 globular proteins in water was determined by means of sound velocity measurements at 25 degrees C. All the proteins studied except for subtilisin showed positive -beta s values, indicating the large internal compressibility of the protein molecules. The intrinsic compressibility of proteins free from the hydration effect appeared to be comparable to that of normal ice. The compressibility data for 25 proteins, including 14 reported previously [Gekko, K., & Noguchi, H. (1979) J. Phys. Chem. 83, 2706-2714], were statistically analyzed to examine the correlation of the compressibility with some structural parameters and the amino acid compositions of proteins. It was found that -beta s increases with increasing partial specific volume and hydrophobicity of proteins. The helix element also seemed to be a dynamic domain to increase -beta s. Four amino acid residues (Leu, Glu, Phe, and His) greatly increased -beta s, and another four (Asn, Gly, Ser, and Thr) decreased it. Some empirical equations were derived for the estimation of the -beta s values of unknown proteins on the basis of their amino acid compositions. The volume fluctuations of proteins revealed by the compressibility data were in the range of 30-200 mL/mol, which corresponded to about 0.3% of the total protein volume. The conformational fluctuation seemed to enhance the thermal stability of proteins.

Amino Acids↗
PubMedDate not supplied

Teleradiology at Gunma University Hospital.

Using NEC MediFile 1000 and the public telephone system, the Department of Radiology of Gunma University Hospital and Saitama Medical School deliver image diagnosis to fellow clinicians and affiliated hospitals. The system consists of digitizing, filing, processing, retrieving and archiving units for radiographs and documents. Images were digitized by CCD and filed in 2 Gbyte double sided optical disk, which can accommodate 500 sheets of 14 x 17 films on 1500 of the smallest size slats without data compression. Image resolution was evaluated by ROC curve using multiple pulmonary nodules. The time taken for image transfer over 24 km was tested with various film sizes, image varieties and data compression rates.

Computer Communication Networks↗
PubMed2005

Performance evaluation of functional medical imaging compression via optimal sampling schedule designs and cluster analysis.

In previous work we have described a technique for the compression of positron emission tomography (PET) image data in the spatial and temporal domains based on optimal sampling schedule designs (OSS) and cluster analysis. It can potentially achieve a high data compression ratio greater than 80:1. However, the number of distinguishable cluster groups in dynamic PET image data is a critical issue for this algorithm that has not been experimentally analyzed on clinical data. In this paper, the problem of experimentally determining the ideal cluster number for the algorithm for PET brain data is addressed.

Algorithms↗
PubMed1990

Detection of ventricular tachycardia using scanning correlation analysis.

Cross correlation is an accurate method for distinguishing normal sinus rhythm (NSR) from ventricular arrhythmias. The computational demands of the method, however, have prohibited development of an implantable device using correlation. In this study, temporal data compression prior to correlation analysis was used to reduce the total number of computations. Unipolar and bipolar intracardiac electrograms of NSR and 23 episodes of ventricular tachycardia (VT) from 23 patients were obtained from a right ventricular apex electrode catheter during routine electrophysiology studies. The data were filtered (1-11 Hz), digitized (250 samples/sec) and temporally compressed to 50 samples/sec. Data compression removed four out of every five samples by only saving the sample with the maximum excursion from the last saved sample. The average squared correlation coefficient (r2) was computed for the NSR and VT episodes using each patient's NSR waveform as a template. In all 23 patients, the r2 values showed large separation between NSR versus VT in both unipolar (0.93 +/- 0.05 vs 0.20 +/- 0.16, P less than 0.005) and bipolar (0.91 +/- 0.07 vs 0.17 +/- 0.11, P less than 0.005) electrode configurations using template lengths of 80% the intrinsic interval (avg +/- SD). Narrow templates (40% intrinsic interval or less) often resulted in multiple r2 peaks during each heart cycle and degraded the r2 separation (n = 10, P less than 0.005). High pass filtering at 3 Hz also degraded the r2 separation (n = 10, P less than 0.05). Standard noncompressed correlations indicated that data compression had negligible effects on the results. Thus, a computationally efficient cross correlation method was found to be a reliable detector of VT.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗