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PubMed2006

On the number of rectangular tilings.

Adaptive multiscale representations via quadtree splitting and two-dimensional (2-D) wavelet packets, which amount to space and frequency decompositions, respectively, are powerful concepts that have been widely used in applications. These schemes are direct extensions of their one-dimensional counterparts, in particular, by coupling of the two dimensions and restricting to only one possible further partition of each block into four subblocks. In this paper, we consider more flexible schemes that exploit more variations of multidimensional data structure. In the meantime, we restrict to tree-based decompositions that are amenable to fast algorithms and have low indexing cost. Examples of these decomposition schemes are anisotropic wavelet packets, dyadic rectangular tilings, separate dimension decompositions, and general rectangular tilings. We compute the numbers of possible decompositions for each of these schemes. We also give bounds for some of these numbers. These results show that the new rectangular tiling schemes lead to much larger sets of 2-D space and frequency decompositions than the commonly-used quadtree-based schemes, therefore bearing the potential to obtain better representation for a given image.

Algorithms↗
PubMed2005

Two improved algorithms with which to obtain contoured windows for fringe patterns generated by electronic speckle-pattern interferometry.

Fringe patterns generated by electronic speckle-pattern interferometry are full of high-spatial-frequency and high-contrast speckle noise. Filtering with contoured windows has proved to be an efficient approach to filtering out speckle noise while retaining the fringe patterns. Furthermore, with contoured windows the contoured correlation fringe pattern method can be used to derive smooth, normalized, consistent fringes. Contoured windows previously were determined by fringe orientation only, and this process generated accumulated errors. We propose two new algorithms with which to obtain the contoured windows according to the fringe intensity slope and the distance ratio to neighboring skeletons. These new techniques can determine contoured windows more precisely.

Algorithms↗
PubMed2000

[Guidelines for cardiopulmonary resuscitation of children].

In this article the European Resuscitation Council's guidelines for basic and advanced resuscitation of children are presented. There are some changes from the previous guidelines. Children are divided in three age categories (in addition to the newly born): children up to one year old, one to eight years old, and more than eight years old. In Norway, but not in the rest of Europe, evaluation of the circulation by pulse check has been eliminated in basic, but not in advanced resuscitation. This is due to reports that pulse checks by lay rescuers require much time with poor specificity and sensitivity. In evaluating the patient's own ventilation, the differentiation between agonal gasps and regular breaths is stressed. ECG monitoring provides the link between paediatric basic life support and advanced life support. The algorithm for the latter closely resembles that proposed for adults. While there were previously three separate algorithms for ventricular fibrillation/ventricular tachycardia, asystole and electromechanical dissociation, there is now only one algorithm. Ventilation and chest compressions should be performed for one-minute periods with ventricular fibrillation/ventricular tachycardia, for three-minute periods with other rhythms.

Adult↗
PubMed2004

Model-based reconstructive elasticity imaging of deep venous thrombosis.

Deep venous thrombosis (DVT) and its sequela, pulmonary embolism, is a significant clinical problem. Once detected, DVT treatment is based on the age of the clot. There are no good noninvasive methods, however, to determine clot age. Previously, we demonstrated that imaging internal mechanical strains can identify and possibly age thrombus in a deep vein. In this study the deformation geometry for DVT elasticity imaging and its effect on Young's modulus estimates is addressed. A model-based reconstruction method is presented to estimate elasticity in which the clot-containing vessel is modeled as a layered cylinder. Compared to an unconstrained approach in reconstructive elasticity imaging, the proposed model-based approach has several advantages: only one component of the strain tensor is used; the minimization procedure is very fast; the method is highly efficient because an analytic solution of the forward elastic problem is used; and the method is not very sensitive to the details of the external load pattern--a characteristic that is important for free-hand, external, surface-applied deformation. The approach was tested theoretically using a numerical model, and experimentally on both tissue-like phantoms and an animal model of DVT. Results suggest that elasticity reconstruction may prove to be a practical adjunct to triplex scanning to detect, diagnose, and stage DVT.

Aging↗
PubMed2001

Indexing huge genome sequences for solving various problems.

Because of the increase in the size of genome sequence databases, the importance of indexing the sequences for fast queries grows. Suffix trees and suffix arrays are used for simple queries. However these are not suitable for complicated queries from huge amount of sequences because the indices are stored in disk which has slow access speed. We propose storing the indices in memory in a compressed form. We use the compressed suffix array. It compactly stores the suffix array at the cost of theoretically a small slowdown in access speed. We experimentally show that the overhead of using the compressed suffix array is reasonable in practice. We also propose an approximate string matching algorithm which is suitable for the compressed suffix array. Furthermore, we have constructed the compressed suffix array of the whole human genome. Because its size is about 2G bytes, a workstation can handle the search index for the whole data in main memory, which will accelerate the speed of solving various problems in genome informatics.

Abstracting and Indexing↗
PubMed2006

The impact of image information on compressibility and degradation in medical image compression.

The aim of the study was to demonstrate and critically discuss the influence of image information on compressibility and image degradation. The influence of image information on image compression was demonstrated on the axial computed tomography images of a head. The standard Joint Photographic Expert Group (JPEG) and JPEG 2000 compression methods were used in compression ratio (CR) and in quality factor (QF) compression modes. Image information was estimated by calculating image entropy, while the effects of image compression were evaluated quantitatively, by file size reduction and by local and global mean square error (MSE), and qualitatively, by visual perception of distortion in high and low contrast test patterns. In QF compression mode, a strong correlation between image entropy and file size was found for JPEG (r=0.87, p < 0.001) and JPEG 2000 (r=0.84, p < 0.001), while corresponding local MSE was constant (4.54) or nearly constant (2.36-2.37), respectively. For JPEG 2000 CR compression mode, CR was nearly constant (1:25), while local MSE varied considerably (2.26 and 10.09). The obtained qualitative and quantitative results clearly demonstrate that image degradation highly depends on image information, which indicates that the degree of image degradation cannot be guaranteed in CR but only in QF compression mode. CR is therefore not a measure of choice for expressing the degree of image degradation in medical image compression. Moreover, even when using QF compression modes, objective evaluation, and comparison of the compression methods within and between studies is often not possible due to the lack of standardization of compression quality scales.

Algorithms↗
PubMed2006

Low-rate and flexible image coding with redundant representations.

New breakthroughs in image coding possibly lie in signal decomposition through nonseparable basis functions that can efficiently capture edge characteristics, present in natural images. The work proposed in this paper provides an adaptive way of representing images as a sum of two-dimensional features. It presents a low bit-rate image coding method based on a matching pursuit (MP) expansion, over a dictionary built on anisotropic refinement and rotation of contour-like atoms. This method is shown to provide, at low bit rates, results comparable to the state of the art in image compression, represented here by JPEG2000 and SPIHT, with generally a better visual quality in the MP scheme. The coding artifacts are less annoying than the ringing introduced by wavelets at very low bit rate, due to the smoothing performed by the basis functions used in the MP algorithm. In addition to good compression performances at low bit rates, the new coder has the advantage of producing highly flexible streams. They can easily be decoded at any spatial resolution, different from the original image, and the bitstream can be truncated at any point to match diverse bandwidth requirements. The spatial adaptivity is shown to be more flexible and less complex than transcoding operations generally applied to state of the art codec bitstreams. Due to both its ability for capturing the most important parts of multidimensional signals, and a flexible stream structure, the image coder proposed in this paper represents an interesting solution for low to medium rate image coding in visual communication applications.

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↗
PubMed1990

Standardized evaluation of techniques for measuring the spectral compression of the myoelectric signal.

A digital algorithm was designed to produce band-limited noise with adjustable median frequency and amplitude. This algorithm produces test signals with spectral characteristics typical of those of the surface myoelectric signals encountered in muscle fatigue studies. These synthesized signals provide the basis for standardized evaluation of the performance of various techniques which monitor the spectral compression of the myoelectric signal during muscle fatigue.

Algorithms↗
PubMed2005

Regression-based prediction for blocking artifact reduction in JPEG-compressed images.

In order to reduce the blocking artifact in the Joint Photographic Experts Group (JPEG)-compressed images, a new noniterative postprocessing algorithm is proposed. The algorithm consists of a two-step operation: low-pass filtering and then predicting. Predicting the original image from the low-pass filtered image is performed by using the predictors, which are constructed based on a broken line regression model. The constructed predictor is a generalized version of the projector onto the quantization constraint set, or the narrow quantization constraint set. We employed different predictors depending on the frequency components in the discrete cosine transform (DCT) domain since each component has different statistical properties. Further, by using a simple classifier, we adaptively applied the predictors depending on the local variance of the DCT block. This adaptation enables an appropriate blurring depending on the smooth or detail region, and shows improved performance in terms of the average distortion and the perceptual view. For the major-edge DCT blocks, which usually suffer from the ringing artifact, the quality of fit to the regression model is usually not good. By making a modification of the regression model for such DCT blocks, we can also obtain a good perceptual view. The proposed algorithm does not employ any sophisticated edge-oriented classifiers and nonlinear filters. Compared to the previously proposed algorithms, the proposed algorithm provides comparable or better results with less computational complexity.

Algorithms↗
PubMed2001

A computational algorithm for computing nonlinear auditory frequency selectivity.

Computational algorithms that mimic the response of the basilar membrane must be capable of reproducing a range of complex features that are characteristic of the animal observations. These include complex input output functions that are nonlinear near the site's best frequency, but linear elsewhere. This nonlinearity is critical when using the output of the algorithm as the input to models of inner hair cell function and subsequent auditory-nerve models of low- and high-spontaneous rate fibers. We present an algorithm that uses two processing units operating in parallel: one linear and the other compressively nonlinear. The output from the algorithm is the sum of the outputs of the linear and nonlinear processing units. Input to the algorithm is stapes motion and output represents basilar membrane motion. The algorithm is evaluated against published chinchilla and guinea pig observations of basilar membrane and Reissner's membrane motion made using laser velocimetry. The algorithm simulates both quantitatively and qualitatively, differences in input/output functions among three different sites along the cochlear partition. It also simulates quantitatively and qualitatively a range of phenomena including isovelocity functions, phase response, two-tone suppression, impulse response, and distortion products. The algorithm is potentially suitable for development as a bank of filters, for use in more comprehensive models of the peripheral auditory system.

Algorithms↗
PubMed1999

A self-organizing algorithm for vector quantizer design applied to signal processing.

Vector quantization plays an important role in many signal processing problems, such as speech/speaker recognition and signal compression. This paper presents an unsupervised algorithm for vector quantizer design. Although the proposed method is inspired in Kohonen learning, it does not incorporate the classical definition of topological neighborhood as an array of nodes. Simulations are carried out to compare the performance of the proposed algorithm, named SOA (self-organizing algorithm), to that of the traditional LBG (Linde-Buzo-Gray) algorithm. The authors present an evaluation concerning the codebook design for Gauss-Markov and Gaussian sources, since the theoretic optimal performance bounds for these sources, as described by Shannon's Rate-Distortion Theory, are known. In speech and image compression, SOA codebooks lead to reconstructed (vector-quantized) signals with better quality as compared to the ones obtained by using LBG codebooks. Additionally, the influence of the initial codebook in the algorithm performance is investigated and the algorithm ability to learn representative patterns is evaluated. In a speaker identification system, it is shown that the the codebooks designed by SOA lead to higher identification rates when compared to the ones designed by LBG.

Algorithms↗
PubMed2005

EM in high-dimensional spaces.

This paper considers fitting a mixture of Gaussians model to high-dimensional data in scenarios where there are fewer data samples than feature dimensions. Issues that arise when using principal component analysis (PCA) to represent Gaussian distributions inside Expectation-Maximization (EM) are addressed, and a practical algorithm results. Unlike other algorithms that have been proposed, this algorithm does not try to compress the data to fit low-dimensional models. Instead, it models Gaussian distributions in the (N - 1)-dimensional space spanned by the N data samples. We are able to show that this algorithm converges on data sets where low-dimensional techniques do not.

Algorithms↗
PubMed2005

Sparse geometric image representations with bandelets.

This paper introduces a new class of bases, called bandelet bases, which decompose the image along multiscale vectors that are elongated in the direction of a geometric flow. This geometric flow indicates directions in which the image gray levels have regular variations. The image decomposition in a bandelet basis is implemented with a fast subband-filtering algorithm. Bandelet bases lead to optimal approximation rates for geometrically regular images. For image compression and noise removal applications, the geometric flow is optimized with fast algorithms so that the resulting bandelet basis produces minimum distortion. Comparisons are made with wavelet image compression and noise-removal algorithms.

Algorithms↗
PubMed2003

Acute cerebral infarction: effect of JPEG compression on detection at CT.

PURPOSE: To evaluate the effect of Joint Photographic Experts Group (JPEG) compression ratios of 10:1 and 20:1 on detection of acute cerebral infarction at computed tomography (CT). MATERIALS AND METHODS: CT images obtained in 25 patients with acute cerebral infarction and 25 patients with no lesions were compressed by means of a JPEG algorithm at ratios of 10:1 and 20:1. Normal and abnormal sections (on original and compressed images) were reviewed by using a color soft-copy computed monochrome cathode ray tube monitor. Five observers rated the presence or absence of a lesion with a 50-point scale (0, definitely absent; 25, equivocal; and 50, definitely present). Diagnostic accuracy was evaluated with receiver operating characteristic (ROC) curve analysis. Significant difference was defined as a P value less than.05 for the area tested with a two-tailed paired Student t test. RESULTS: At ROC analysis, no statistically significant difference was detected for all cases considered together (Az [area under the ROC curve] = 0.887 +/- 0.038 [mean +/- SD] on noncompressed images, Az = 0.897 +/- 0.038 on 10:1 compressed images, and Az = 0.842 +/- 0.073 on 20:1 compressed images; P >.05). CONCLUSION: JPEG compression at ratios of 10:1 and 20:1 was tolerated in the detection of acute cerebral infarction at CT.

Acute Disease↗
PubMed2005

A web service-based Grid portal for Edgebreaker compression.

BACKGROUND: In health applications, and elsewhere, 3D data sets are increasingly accessed through the Internet. To reduce the transfer time while maintaining an unaltered 3D model, adequate compression and decompression techniques are needed. Recently, Grid technologies have been integrated with Web Services technologies to provide a framework for interoperable application-to-application interaction. OBJECTIVES: The paper describes an implementation of the Edgebreaker compression technique exploiting web services technology and presents a novel approach for using such services in a Grid Portal. The Grid portal, developed at the CACT/ISUFI of the University of Lecce, allows the processing and delivery of biomedical images (CT--computerized tomography--and MRI--magnetic resonance images) in a distributed environment, using the power and security of computational Grids. METHODS: The Edgebreaker Compression Web Service has been deployed on a Grid portal and allows compressing and decompressing 3D data sets using the Globus toolkit GSI (Globus Security Infrastructure) protocol. Moreover, the classical algorithm has been modified extending the compression to files containing more than one object. RESULTS AND CONCLUSIONS: An implementation of the Edgebreaker compression technique and related experimental results are presented. A novel approach for using the compression web service in a Grid portal allowing storing and preprocessing of huge 3D data sets, and subsequent efficient transmission of results for remote visualization is also described.

Algorithms↗
PubMed2002

Clinical evaluation of compression ratios using JPEG2000 on computed radiography chest images.

The efficient compression of radiographic images is of importance for improved storage and network utilization in support of picture archiving and communication systems (PACS) applications. The DICOM Working Group 4 adopted JPEG2000 as an additional compression standard in Supplement 61 over the existing JPEG. The wavelet-based JPEG2000 can achieve higher compression ratios with less distortion than the Discrete Cosine Transform (DCT)-based JPEG algorithm. However, the degradation of JPEG2000-compressed computed radiography (CR) chest images has not been tested comprehensively clinically. The authors evaluated the diagnostic quality of JPEG2000-compressed CR chest images with compression ratios from 5:1 to 200:1. An ROC (receiver operating characteristic analysis) and t test were performed to ascertain clinical performance using the JPEG2000-compressed images. The authors found that compression ratios as high as 20:1 can be utilized without affecting lesion detectability. Significant differences between the original and the compressed CR images were not recognized up to compression ratio of 50:1 within a confidence level of 99%.

Algorithms↗
PubMed2000

Wavelet compression on detection of brain lesions with magnetic resonance imaging.

The purpose of this report is to assess clinically acceptable compression ratios on the detection of brain lesions at magnetic resonance imaging (MRI). Four consecutive T2-weighted and the corresponding T1-weighted images obtained in 20 patients were studied for 109 anatomic sites including 50 with lesions and 59 without lesions. The images were obtained on a 1.5-T MR unit with a pixel size of 0.9 to 1.2 x 0.47 mm and a section thickness of 5 mm. The image data were compressed by wavelet-based algorithm at ratios of 20:1, 40:1, and 60:1. Three radiologists reviewed these images on an interactive workstation and rated the presence or absence of a lesion with a 50 point scale for each anatomic site. The authors also evaluated the influence of pixel size on the quality of image compression. At receiver operating characteristic (ROC) analysis, no statistically significant difference was detected at a compression ratio of 20:1. A significant difference was observed with 40:1 compressed images for one reader (P = .023), and with 60:1 for all readers (P = .001 to .012). A root mean squared error (RMSE) was higher in 0.94- x 0.94-mm pixel size images than in 0.94- x 0.47-mm pixel size images at any compression ratio, indicating compression tolerance is lower for the larger pixel size images. The RMSE, subjective image quality, and error images of 10:1 compressed 0.94- x 0.94-mm pixel size images were comparable with those of 20:1 compressed 0.94- x 0.47-mm pixel size images. Wavelet compression can be acceptable clinically at ratios as high as 20:1 for brain MR images when a pixel size at image acquisition is around 1.0 x 0.5 mm, and as high as 10:1 for those with a pixel size around 1.0 x 1.0 mm.

Algorithms↗