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PubMed1993

Discovering simple DNA sequences by the algorithmic significance method.

A new method, 'algorithmic significance', is proposed as a tool for discovery of patterns in DNA sequences. The main idea is that patterns can be discovered by finding ways to encode the observed data concisely. In this sense, the method can be viewed as a formal version of the Occam's Razor principle. In this paper the method is applied to discover significantly simple DNA sequences. We define DNA sequences to be simple if they contain repeated occurrences of certain 'words' and thus can be encoded in a small number of bits. Such definition includes minisatellites and microsatellites. A standard dynamic programming algorithm for data compression is applied to compute the minimal encoding lengths of sequences in linear time. An electronic mail server for identification of simple sequences based on the proposed method has been installed at the Internet address pythia/anl.gov.

Algorithms↗
PubMed1991

Relation of mean pixel intensity to concentration of sonicated albumin microspheres: effects of ultrasound system settings.

Myocardial contrast echocardiography (MCE) is a recently developed technique to assess myocardial perfusion. Previous studies have shown that MCE frequently underestimates coronary reserve as compared with other methods. Previous reports have suggested that some of the limitations of MCE are due to the nonlinear processing algorithms of the ultrasound systems. Therefore we designed an in vitro model to study the effects of various processing algorithms and levels of acoustic power (AP) on the relation between concentration of echocontrast and mean pixel intensities. A beaker containing a commercially produced, diluted solution of sonicated albumin microspheres was imaged with a commercial Hewlett Packard ultrasound system, and mean pixel intensities were determined with an off-line computer system. The solution was imaged at a wide range of APs (40-10 dB) and time gain compensation (40-60 dB). Concentration versus intensity curves were generated using all possible combinations of compression and processing algorithms available on the ultrasound system used. Contrast effect diminished rapidly when exposed to high AP. Lower powers had less effect on contrast intensity duration, with no effect seen below 20 dB. Changes in time gain compensation did not affect contrast intensities. Regardless of the processing algorithm examined, the relation between concentration of echocontrast and mean pixel intensities was near linear in the first two to three concentrations; thereafter, the curves flattened during increasing concentrations of contrast. At higher concentrations, acoustic shadowing produced a decrease in pixel intensities.(ABSTRACT TRUNCATED AT 250 WORDS)

Acoustics↗
PubMed2006

[Basic life support in pediatrics].

Basic life support (BLS) is the combination of maneuvers that identifies the child in cardiopulmonary arrest and initiates the substitution of respiratory and circulatory function, without the use of technical adjuncts, until the child can receive more advanced treatment. BLS includes a sequence of steps or maneuvers that should be performed sequentially: ensuring the safety of rescuer and child, assessing unconsciousness, calling for help, positioning the victim, opening the airway, assessing breathing, ventilating, assessing signs of circulation and/or central arterial pulse, performing chest compressions, activating the emergency medical service system, and checking the results of resuscitation. The most important changes in the new guidelines are the compression: ventilation ratio and the algorithm for relieving foreign body airway obstruction. A compression/ ventilation ratio of 30:2 will be recommended for lay rescuers of infants, children and adults. Health professionals will use a compression: ventilation ratio of 15:2 for infants and children. If the health professional is alone, he/she may also use a ratio of 30:2 to avoid fatigue. In the algorithm for relieving foreign body airway obstruction, when the child becomes unconscious, the maneuvers will be similar to the BLS sequence with chest compressions (functioning as a deobstruction procedure) and ventilation, with reassessment of the mouth every 2 min to check for a foreign body, and evaluation of breathing and the presence of vital signs. BLS maneuvers are easy to learn and can be performed by anyone with adequate training. Therefore, BLS should be taught to all citizens.

Algorithms↗
PubMedDate not supplied

Vector quantization as a method for integer EMG signal compression.

Vector quantization (VQ) is a well-known lossy compression method, which has not often been applied to biosignals. In this paper, VQ and its mean residual variant for encoding and decoding electromyography (EMG) signals have been tested. The methods are selected in such a way that they can be later applied in a low-resource embedded system. A neural network approach is used for codebook generation. The preservation of medical parameters is a prominent sign of quality in medical compression systems. Both signal level fidelity factors and preserving medical parameters are tested. The results show that mean residual vector quantization with short segments is a workable approach for EMG signal compression.

Algorithms↗
PubMedDate not supplied

[Possibilities of using telemedicine in preoperative examination of the lens nucleus density].

The MPEG-4 algorithm applicable to compression of video-images of the anterior eye segment and JPEG-2000 applicable to compression of static images of the lens and retina under the conditions of mydriasis were used to enable the telemedicine consultations. The compiled compression files were sent to the institute's E-Mail address by means of a voice modem through an analogue telephone line. The pixel structures of non-compression and compression images of the anterior eye segment and lenses were comparatively studied. The deviations of images' optic density versus non-compression images were found to be below or equal to 2.7%, thus, they can be attributed to a static error. The quantitative colorimetry of images was used, on the basis of a software-based color-regulating filter, to determine the lens-nucleus density and cataract-maturity degree. The differences between values of the green-canal brightness were found within the RGB model before and after the application of the filter in the posterior cortical strata and in the anterior lens-nucleus portion, which provided for classifying 6 stages of the lens-nucleus density and cataract maturity.

Algorithms↗
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↗
PubMed1993

Compensation for the signal processing characteristics of ultrasound B-mode scanners in adaptive speckle reduction.

A systematic method to compensate for nonlinear amplification of individual ultrasound B-scanners has been investigated in order to optimise performance of an adaptive speckle reduction (ASR) filter for a wide range of clinical ultrasonic imaging equipment. Three potential methods have been investigated: (1) a method involving an appropriate selection of the speckle recognition feature was successful when the scanner signal processing executes simple logarithmic compressions; (2) an inverse transform (decompression) of the B-mode image was effective in correcting for the measured characteristics of image data compression when the algorithm was implemented in full floating point arithmetic; (3) characterising the behaviour of the statistical speckle recognition feature under conditions of speckle noise was found to be the method of choice for implementation of the adaptive speckle reduction algorithm in limited precision integer arithmetic. In this example, the statistical features of variance and mean were investigated. The third method may be implemented on commercially available fast image processing hardware and is also better suited for transfer into dedicated hardware to facilitate real-time adaptive speckle reduction. A systematic method is described for obtaining ASR calibration data from B-mode images of a speckle producing phantom.

Algorithms↗
PubMedDate not supplied

Digitization of medical documents: an X-Windows application for fast scanning.

This paper deals with digitization, using a commercial scanner, of medical documents as still images for introduction into a computer-based Information System. Document management involves storing, editing and transmission. This task has usually been approached from the perspective of the difficulties posed by radiologic images because of their indisputable qualitative and quantitative significance. However, healthcare activities require the management of many other types of documents and involve the requirements of numerous users. One key to document management will be the availability of a digitizer to deal with the greatest possible number of different types of documents. This paper describes the relevant aspects of documents and the technical specifications that digitizers must fulfill. The concept of document type is introduced as the ideal set of digitizing parameters for a given document. The use of document type parameters can drastically reduce the time the user spends in scanning sessions. Presentation is made of an application based on Unix, X-Windows and OSF/Motif, with a GPIB interface, implemented around the document type concept. Finally, the results of the evaluation of the application are presented, focusing on the user interface, as well as on the viewing of color images in an X-Windows environment and the use of lossy algorithms in the compression of medical images.

Database Management Systems↗
PubMed1999

Location of repetitive regions in sequences by optimizing a compression method.

Suppose that a biologist wishes to study some local property P of genetic sequences. If he can design (with a computer scientist) an algorithm C which efficiently compresses parts of the sequence which satisfy P, then our algorithm TurboOptLift locates very quickly where property P occurs by chance on a sequence, and where it occurs as a result of a significant process. Under some conditions, the time complexity of TurboOptLift is O(n log n). We illustrate its use on the practical problem of locating approximate tandem repeats in DNA sequences.

Algorithms↗
PubMed1997

An analytical look at the effects of compression on medical images.

This article will take an analytical look at how lossy Joint Photographic Experts Group (JPEG) and wavelet image compression techniques affect medical image content. It begins with a brief explanation of how the JPEG and wavelet algorithms work, and describes in general terms what effect they can have on image quality (removal of noise, blurring, and artifacts). It then focuses more specifically on medical image diagnostic content and explains why subtle pathologies, that may be difficult for the human eye to discern because of low contrast, are generally very well preserved by these compression algorithms. By applying a wavelet decomposition to the whole image and to specific regions of interest (ROI), and by understanding how the lossy quantization step attenuates signals in those decomposition energy subbands, much can be learned about how tolerant various anatomical structures are to compression. High-frequency anatomical structures that have their energy represented by a few large coefficients (in the wavelet domain) will be well preserved, while, those structures with high frequency energy distributed over numerous smaller coefficients are the most vulnerable to compression. Digitized films showing subtle chest nodules, a subtle stress fracture, and CT and MR images are used to show these results.

Algorithms↗
PubMed2000

Effect of CT digital image compression on detection of coronary artery calcification.

PURPOSE: To test the effect of digital compression of CT images on the detection of small linear or spotted high attenuation lesions such as coronary artery calcification (CAC). MATERIAL AND METHODS: Fifty cases with and 50 without CAC were randomly selected from a population that had undergone spiral CT of the thorax for screening lung cancer. CT image data were compressed using JPEG (Joint Photographic Experts Group) or wavelet algorithms at ratios of 10:1, 20:1 or 40:1. Five radiologists reviewed the uncompressed and compressed images on a cathode-ray-tube. Observer performance was evaluated with receiver operating characteristic analysis. RESULTS: CT images compressed at a ratio as high as 20:1 were acceptable for primary diagnosis of CAC. There was no significant difference in the detection accuracy for CAC between JPEG and wavelet algorithms at the compression ratios up to 20:1. CT images were more vulnerable to image blurring on the wavelet compression at relatively lower ratios, and "blocking" artifacts occurred on the JPEG compression at relatively higher ratios. CONCLUSION: JPEG and wavelet algorithms allow compression of CT images without compromising their diagnostic value at ratios up to 20:1 in detecting small linear or spotted high attenuation lesions such as CAC, and there was no difference between the two algorithms in diagnostic accuracy.

Adult↗
PubMed2005

HVS-based medical image compression.

INTRODUCTION: With the promotion and application of digital imaging technology in the medical domain, the amount of medical images has grown rapidly. However, the commonly used compression methods cannot acquire satisfying results. METHODS: In this paper, according to the existed and stated experiments and conclusions, the lifting step approach is used for wavelet decomposition. The physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in human vision system (HVS), and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. RESULTS: The experiments are done on the medical images including computed tomography (CT) and magnetic resonance imaging (MRI). At the same bit rate, the performance of SPIHT, with respect to the PSNR metric, is significantly higher than that of our algorithm. But the visual quality of the SPIHT-compressed image is roughly the same as that of the image compressed with our approach. Our algorithm obtains the same visual quality at lower bit rates and the coding/decoding time is less than that of SPIHT. CONCLUSIONS: The results show that under common objective conditions, our compression algorithm can achieve better subjective visual quality, and performs better than that of SPIHT in the aspects of compression ratios and coding/decoding time.

Algorithms↗
PubMed2002

Computationally inexpensive methods for intra-cardiac atrial bipolar electrogram compression.

AIM: This paper reports studies of mathematical algorithms for intra-cardiac atrial bipolar electrogram compression suitable with implementation on implantable devices. PATIENTS AND METHODS: Bipolar intra-cardiac electrograms (IEGMs) of high right atrium were obtained from 20 patients who underwent electrophysiological studies for arrhythmias. Four thousand seven hundred and eighty-two seconds of IEGM were collected and divided into three rhythm groups: sinus rhythm (SR), atrial fibrillation (AF) and atrial flutter (AFL). Since mathematical algorithms suitable for use with implantable devices demand low computational cost, we employed piecemeal linear approximation methods (ZOP--Zero Order Prediction and SAPA--Scan Along Polygonal Approximation), and beat detection method (Peak) both or which need small numbers of operations to perform electrogram compression. Compression ratio (CR) and percent root mean square difference (PRD) were used to compare the three methods, with statistical analyses performed using paired t-test. RESULTS AND CONCLUSION: The best performance was obtained using the Peak method which reaches an average CR of 10.6 in the case of SR group, 2.8 for AF, and 3.6 for AFL groups, respectively, while PRD lies below 2% for SR and AFL groups and 6% for the AF group. Results show that, for bipolar electrograms, the Peak method reaches statistically significant better performance (P<0.001) in all cases except for Peak vs SAPA applied to AF (P=0.2). The number of operations necessary to compress the data indicate that time consumption can be reduced to be suitable for real time compression in implantable devices. The Peak method, which was assumed to receive the instant of occurrence of each recognized beat, from the hardware of the device, requires fewer operations than ZOP and SAPA. Increasing the length of electrograms recorded in pacemakers will enhance the amount of information provided by the implantable device, allowing more detailed characterization of the intra-cardiac activity and leading to new perspectives in arrhythmia diagnosis and therapy.

Adult↗
PubMedDate not supplied

On lossy transform compression of ECG signals with reference to deformation of their parameter values.

Electrocardiogram (ECG) signals are the most prominent biomedical signal type used in clinical medicine. Their compression is important and widely researched in the medical informatics community. In the previous literature compression efficacy has been investigated only in the context of how much known or developed methods reduced the storage required by compressed forms of original ECG signals. Sometimes statistical signal evaluations based on, for example, root mean square error were studied. In previous research we developed a refined method for signal compression and tested it jointly with several known techniques for other biomedical signals. Our method of so-called successive approximation quantization used with wavelets was one of the most successful in those tests. In this paper, we studied to what extent these lossy compression methods altered values of medical parameters (medical information) computed from signals. Since the methods are lossy, some information is lost due to the compression when a high enough compression ratio is reached. We found that ECG signals sampled at 400 Hz could be compressed to one fourth of their original storage space, but the values of their medical parameters changed less than 5% due to compression, which indicates reliable results.

Algorithms↗
PubMed1987

Image compression for medical imaging systems.

The physical size of typical digital images, in terms of the number of bytes of data one image contains, is large; e.g., a 1024 X 1024 image with 8 bits of data per pixel contains a megabyte of data. To transmit many such images over a network, sometimes over low-capacity phone lines to remote sites, or to store large numbers of images over a long period of time as part of the medical records for patients, the need for image compression arises to alleviate these large demands for image data storage and transmission capacity. This paper discusses image compression in terms of the information theory upon which it is based. The two basic categories of algorithms for implementing image compression are presented along with considerations for image quality and accuracy, which are of primary importance to the medical imaging community.

Diagnostic Imaging↗
PubMed2002

Using contexts and R-R interval estimation in lossless ECG compression.

The paper presents a new lossless ECG compression scheme. The short-term predictor and the coder use conditioning on a small number of contexts. The long-term prediction is based on an algorithm for R-R interval estimation. Several QRS detection algorithms are investigated to select a low complexity and reliable detection algorithm. The coding of prediction residuals uses primarily the Golomb-Rice (GR) codes, but, to improve the coding results, escape codes GR-ESC are used in some contexts for a limited number of samples. Experimental results indicate the good overall performance of the lossless ECG compression algorithms (reducing the storage needs from 12 to about 3-4 bits per sample). The scheme consistently outperforms other waveform or general purpose coding algorithms.

Algorithms↗
PubMed2001

Effect of wavelet compression on data transmission in a multipurpose wireless telemedicine system.

We have developed a novel emergency telemedicine system which allows the transmission of physiological data (electrocardiogram, oximetry, blood pressure and temperature) and still images of the patient. The transmission is performed through wireless links using either GSM mobile phones or satellite. Because of the low bandwidth available through these links, data compression is required to allow realtime transmission of electrocardiographic (ECG) data. A new integrated design approach for an optimal zonal wavelet compression (OZWC) method was implemented for the ECG data. The performance of the mobile system with compressed ECG data segments was evaluated in terms of the percentage root-mean-square difference and visual inspection. The optimum wavelet algorithm achieved a maximum compression ratio of 18:1 with low distortion.

Algorithms↗
PubMed2005

Deblocking of block-transform compressed images using weighted sums of symmetrically aligned pixels.

A new class of related algorithms for deblocking block-transform compressed images and video sequences is proposed in this paper. The algorithms apply weighted sums on pixel quartets, which are symmetrically aligned with respect to block boundaries. The basic weights, which are aimed at very low bit-rate images, are obtained from a two-dimensional function which obeys predefined constraints. Using these weights on images compressed at higher bit rates produces a deblocked image which contains blurred "false" edges near real edges. We refer to this phenomenon as the ghosting effect. In order to prevent its occurrences, the weights of pixels, which belong to nonmonotone areas, are modified by dividing each pixel's weight by a predefined factor called a grade. This scheme is referred to as weight adaptation by grading (WABG). Better deblocking of monotone areas is achieved by applying three iterations of the WABG scheme on such areas followed by a fourth iteration which is applied on the rest of the image. We refer to this scheme as deblocking frames of variable size (DFOVS). DFOVS automatically adapts itself to the activity of each block. This new class of algorithms produces very good subjective results and PSNR results which are competitive relative to available state-of-the-art methods.

Algorithms↗