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PubMed2001

Effects of JPEG and wavelet compression of spiral low-dose ct images on detection of small lung cancers.

PURPOSE: To compare the effect of compression of spiral low-dose CT images by the Joint Photographic Experts Group (JPEG) and wavelet algorithms on detection of small lung cancers. MATERIAL AND METHODS: Low-dose spiral CT images of 104 individuals (52 with peripheral lung cancers smaller than 20 mm and 52 control subjects) were used. The original images were compressed using JPEG or wavelet algorithms at a ratio of 10:1 or 20:1. Five radiologists interpreted these images and evaluated the image quality on a high-resolution CRT monitor. Observer performance was studied by receiver operating characteristic (ROC) analysis. RESULTS: There was no significant difference in the detection of cancers measuring 6 to 15 mm in uncompressed images and in those compressed by either of the algorithms, although the quality of images compressed at 20:1 with the wavelet algorithm was somewhat inferior. A lower diagnostic accuracy was noted using images compressed by the JPEG or wavelet algorithms at 20:1 in detecting lung cancers measuring 6 to 10 mm and cancers measuring from 6 to 15 mm with ground-glass opacity. CONCLUSION: Compression of low-dose CT images at a ratio of 10:1 using JPEG and wavelet algorithms does not compromise the detection rate of small lung cancers.

Algorithms↗
PubMed2006

Adaptive downsampling to improve image compression at low bit rates.

At low bit rates, better coding quality can be achieved by downsampling the image prior to compression and estimating the missing portion after decompression. This paper presents a new algorithm in such a paradigm, based on the adaptive decision of appropriate downsampling directions/ratios and quantization steps, in order to achieve higher coding quality with low bit rates with the consideration of local visual significance. The full-resolution image can be restored from the DCT coefficients of the downsampled pixels so that the spatial interpolation required otherwise is avoided. The proposed algorithm significantly raises the critical bit rate to approximately 1.2 bpp, from 0.15-0.41 bpp in the existing downsample-prior-to-JPEG schemes and, therefore, outperforms the standard JPEG method in a much wider bit-rate scope. The experiments have demonstrated better PSNR improvement over the existing techniques before the critical bit rate. In addition, the adaptive mode decision not only makes the critical bit rate less image-independent, but also automates the switching coders in variable bit-rate applications, since the algorithm turns to the standard JPEG method whenever it is necessary at higher bit rates.

Algorithms↗
PubMedDate not supplied

Digital storage of echocardiograms offers superior image quality to analog storage, even with 20:1 digital compression: results of the Digital Echo Record Access Study.

A large interobserver and intraobserver variability study was performed comparing both digitally compressed and uncompressed echocardiographic images with the same images recorded onto super-VHS video-cassette tape (the current standard). In a blinded, randomized fashion, 179 observers scored the diagnostic and image quality of 20 pairs of echocardiographic loops representing various pathologic conditions. Overall, the digital images were preferred to the S-VHS images both for image quality and diagnostic content (p < 0.0001) regardless of the background or experience level of the observer. Furthermore, uncompressed digital images and those compressed by the Joint Photographic Experts Group (JPEG) algorithm at ratios of 20:1 were judged equivalent. These findings show that digital compression may be used routinely in echocardiography, resulting in improved image and diagnostic quality over present standards.

Adult↗
PubMed2006

Conformational flexibility, hydration and state parameter fluctuations of fibroblast growth factor-10: effects of ligand binding.

Differential effects of ligand binding on local and global fibroblast growth factor-10 (FGF-10) flexibility and stability have been investigated utilizing a variety of experimental and computational techniques. Normal mode analysis was used to predict the low frequency motions and regional flexibility of FGF-10. Similarly, regional variations in local folding/unfolding equilibria were characterized with the COREX/BEST algorithm. Experimental adiabatic and isothermal compressibilities of FGF-10 alone and in the presence of polyanions are compared. Furthermore, the effect of polyanions on the coefficient of thermal expansion is compared. Measurements of density, heat capacity, compressibility, and expansibility were combined to calculate experimentally determined volume and enthalpy fluctuations. Global effects of polyanions on FGF-10 flexibility, thermodynamic fluctuations, and hydration vary depending on the size and charge density of the polyanion. Local effects of polyanions were investigated utilizing time-resolved fluorescence spectroscopy and red edge excitation spectroscopy (REES). Increased rigidity of the protein matrix or an increased solvent response surrounding the Trp residues is observed in the presence of polyanions. Similarly, time-resolved spectroscopy reveals increased ground state heterogeneity and increased dipole relaxation on the time scale of fluorescence for FGF-10 in the presence of polyanions. These polyanions increase heterogeneity, global flexibility, and fluctuations while increasing the melting temperature (Tm) of FGF-10.

Crystallography, X-Ray↗
PubMed2000

Medical image compression by cosine and wavelet transforms.

The investigation results for improving lossy compression techniques for ultrasound and angiographic images are presented. The goal was to clear out where the compression process could be improved for the medical application, and to make efforts to improve it. It is proved that wavelet transform outperforms discrete cosine transform applied for ultrasound and angiographic images. A lot of wavelet classes were tried for choosing the best one suited for corresponding image classes, which were characterized by content complexity criterion. The analysis of international image compression standards was carried out. Special attention was paid to algorithmical and high level service structure of a new still image compression standard JPEG2000. Its open architecture enables including some wavelet classes which we would like to suggest for medical images.

Algorithms↗
PubMed2003

Wavelet coding of volumetric medical datasets.

Several techniques based on the three-dimensional (3-D) discrete cosine transform (DCT) have been proposed for volumetric data coding. These techniques fail to provide lossless coding coupled with quality and resolution scalability, which is a significant drawback for medical applications. This paper gives an overview of several state-of-the-art 3-D wavelet coders that do meet these requirements and proposes new compression methods exploiting the quadtree and block-based coding concepts, layered zero-coding principles, and context-based arithmetic coding. Additionally, a new 3-D DCT-based coding scheme is designed and used for benchmarking. The proposed wavelet-based coding algorithms produce embedded data streams that can be decoded up to the lossless level and support the desired set of functionality constraints. Moreover, objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy and lossless compression results when compared with the state-of-the-art.

Algorithms↗
PubMed2005

The context-tree kernel for strings.

We propose a new kernel for strings which borrows ideas and techniques from information theory and data compression. This kernel can be used in combination with any kernel method, in particular Support Vector Machines for string classification, with notable applications in proteomics. By using a Bayesian averaging framework with conjugate priors on a class of Markovian models known as probabilistic suffix trees or context-trees, we compute the value of this kernel in linear time and space while only using the information contained in the spectrum of the considered strings. This is ensured through an adaptation of a compression method known as the context-tree weighting algorithm. Encouraging classification results are reported on a standard protein homology detection experiment, showing that the context-tree kernel performs well with respect to other state-of-the-art methods while using no biological prior knowledge.

Algorithms↗
PubMed2005

Transform and embedded coding techniques for maximum efficiency and random accessibility in 3-D scalable compression.

This study investigates random accessibility and efficiency enhancements in highly scalable video and volumetric compression. With the advent of interactive multimedia technology, random accessibility has emerged as an increasingly important consideration in the design and optimization process. In this paper, we assess the impact that the transform, embedded coding components, and code-block configurations have on the compression efficiency and accessibility of a scalable codestream. We develop performance bounds on techniques which exploit temporal redundancy within the confines of a feed-forward compression system. We also examine their random access properties to argue the significance of motion-adaptive subband transforms. When information-theoretic measures are used to determine the potential benefits of three-dimensional (3-D) context coding, we find that most of the coding gain is attributed to code-block extension, rather than interslice context modeling itself. To gain further insight into the tradeoffs that the coding part has to offer, we run a series of simulations to determine code-block partitioning strategies which maximize reconstruction quality and space-time localization. The LIMAT framework and EBCOT coding paradigm have laid a solid foundation for further progress in the development of highly scalable 3-D compression systems.

Algorithms↗
PubMed1997

ECG compression and recognition using complete tree representation.

This paper deals with a novel method of Electrocardiogram (ECG) representation, compression and recognition using Complete Tree algorithm. The construction of Complete Tree is like overlaying a ECG waveform on a grid. The waveform is observed through the grid structure with vertical and horizontal grid lines. In addition to nodes created for each interval enclosed by that waveform on a quantisation level, nodes are also created for each point where the waveform cuts the vertical grid line between the current quantisation level and the next quantisation level. A leaf node represents the data sample of ECG at that position. For reconstruction of this ECG waveform, only the leaf nodes are used resulting in ECG compression. This representation is also useful in ECG pattern matching and recognition without reconstructing the original waveform. The ECGs with sampling rate of 500 sps are used. A compression ratio (CR) of 4.8:1 with percent RMS difference (PRD) of 8.45% is obtained. The reconstruction of original ECG waveform from its tree representation shows high fidelity in all its complexes of ECG. The results are compared with all other compression techniques such as AZTEC, TP, FAN, DPCM etc. By using Tree merging and splitting algorithms, the matching and recognition of ECG is implemented.

Algorithms↗
PubMed2000

Quality driven gold washing adaptive vector quantization and its application to ECG data compression.

The gold washing (GW) adaptive vector quantization (AVQ) (GW-AVQ) is a relatively new scheme for data compression. The adaptive nature of the algorithm provides the robustness for wide variety of the signals. However, the performance of GW-AVQ is highly dependent on a preset parameter called distortion threshold (dth) which must be determined by experience or trial-and-error. We propose an algorithm that allows us to assign an initial dth arbitrarily and then automatically progress toward a desired dth according to a specified quality criterion, such as the percent of root mean square difference (PRD) for electrocardiogram (ECG) signals. A theoretical foundation of the algorithm is also presented. This algorithm is particularly useful when multiple GW-AVQ codebooks and, thus, multiple dth's are required in a subband coding framework. Four sets of ECG data with entirely different characteristics are selected from the MIT/BIH database to verify the proposed algorithm. Both the direct GW-AVQ and a wavelet-based GW-AVQ are tested. The results show that a user specified PRD can always be reached regardless of the ECG waveforms, the initial selection of dth or whether a wavelet transform is used in conjunction with the GW-AVQ. An average result of 6% in PRD and 410 bits/s in compressed data rate is obtained with excellent visual quality.

Algorithms↗
PubMed2001

Ultrasound and angio image compression by cosine and wavelet transforms.

The investigation results for improving lossy compression techniques for ultrasound and angio images are presented. The goal was to determine where the compression process could be improved for the medical application, and to make efforts to improve it. It is proved that the wavelet transform outperforms the discrete cosine transform applied to ultrasound and angio images. A lot of wavelet classes were tried for choosing the best one suited for corresponding image classes, which were characterised by a content complexity criterion. The analysis of international image compression standards was carried out. Special attention was paid to an algorithmical and high level service structure of a new still image compression standard JPEG2000. Its open architecture enables including some wavelet classes which we would like to suggest for medical images. A set of recommendations for acceptable compression ratio for different medical image modalities was developed. It was carried out on the base of compression study performed by the group of angiologists and cardiologists.

Algorithms↗
PubMed2006

Adaptive threshold-based block classification in medical image compression for teleradiology.

Telemedicine, among other things, involves storage and transmission of medical images, popularly known as teleradiology. Due to constraints on bandwidth and storage capacity, a medical image may be needed to be compressed before transmission/storage. Among various compression techniques, transform-based techniques that convert an image in spatial domain into the data in spectral domain are very effective. Discrete cosine transform (DCT) is possibly the most popular transform used in compression of images in standards like Joint Photographic Experts Group (JPEG). In DCT-based compression the image is split into smaller blocks for computational simplicity. The blocks are classified on the basis of information content to maximize compression ratio without sacrificing diagnostic information. The present paper presents a technique along with computational algorithm for classification of blocks on the basis of an adaptive threshold value of variance. The adaptive approach makes the classification technique applicable across the board to all medical images. Its efficacy is demonstrated by applying it to CT, X-ray and ultrasound images and by comparing the results against the JPEG in terms of various objective quality indices.

Algorithms↗
PubMed2004

Perceptually tuned JPEG coder for echocardiac image compression.

In this work, we propose an efficient framework for compressing and displaying medical images. Image compression for medical applications, due to available Digital Imaging and Communications in Medicine requirements, is limited to the standard discrete cosine transform-based joint picture expert group. The objective of this work is to develop a set of quantization tables (Q tables) for compression of a specific class of medical image sequences, namely echocardiac. The main issue of concern is to achieve a Q table that matches the specific application and can linearly change the compression rate by adjusting the gain factor. This goal is achieved by considering the region of interest, optimum bit allocation, human visual system constraint, and optimum coding technique. These parameters are jointly optimized to design a Q table that works robustly for a category of medical images. Application of this approach to echocardiac images shows high subjective and quantitative performance. The proposed approach exhibits objectively a 2.16-dB improvement in the peak signal-to-noise ratio and subjectively 25% improvement over the most useable compression techniques.

Algorithms↗
PubMed2006

[An improved motion estimation of medical image series via wavelet transform].

The compression of medical image series is very important in telemedicine. The motion estimation plays a key role in the video sequence compression. In this paper, an improved square-diamond search (SDS) algorithm is proposed for the motion estimation of medical image series. The improved SDS algorithm reduces the number of the searched points. This improved SDS algorithm is used in wavelet transformation field to estimate the motion of medical image series. A simulation experiment for digital subtraction angiography (DSA) is made. The experiment results show that the algorithm accuracy is higher than that of other algorithms in the motion estimation of medical image series.

Algorithms↗
PubMed1999

Digital imaging in remote diagnosis of burns.

Images are capable of giving an accurate representation of skin color and have been used extensively in teaching about and researching burn therapy. The advance from analogue to digital imaging allows the remote transmission of the clinical information contained in the digital image of a burn, using a suitable system. The large size of these image files reduces transmission speed and makes data compression desirable. Compression, by means of the JPEG algorithm, of up to 50 times the original size of 38 digital images of burns suffered by 22 consecutive patients did not lessen its great usefulness in determining the depth of burn injuries, according to a group of experts in burn care. The success rate was close to 90%, both for non-compressed images in original BMP format (mean size:1500 Kb) and for compressed images with a Q index of 50 (30 Kb files), when compared with the clinical diagnoses confirmed one week after the accident.

Adult↗
PubMed2002

An effective coding technique for the compression of one-dimensional signals using wavelet transforms.

This paper introduces an effective technique for the compression of one-dimensional signals using wavelet transforms. It is based on generating a binary stream of 1s and 0s that encodes the wavelet coefficients structure (i.e., encodes the locations of zero and nonzero coefficients). A new coding algorithm, similar to the run length encoding, has been developed for the compression of the binary stream. The compression performances of the technique are measured using compression ratio (CR) and percent root-mean square difference (PRD) measures. To assess the technique properly we have evaluated the effect of signal length, threshold levels selection and wavelet filters on the quality of the reconstructed signal. The effect of finite word length representation on the compression ratio and PRD is also discussed. The technique is tested for the compression of normal and abnormal electrocardiogram (ECG) signals. The performance parameters of the proposed coding algorithm are measured and compression ratios of 19:1 and 45:1 with PRDs of 1% and 2.8% are achieved, respectively. At the receiver end, the received signal is decoded and inverse transformed before being processed. Finally, the merits and demerits of the technique are discussed.

Algorithms↗
PubMed1994

Numerical simulation of unsteady laminar flow through a tilting disk heart valve: prediction of vortex shedding.

Heart valves induce flow disturbances which play a role in blood cell activation and damage, but questions of the magnitude and spatial distribution of fluid stresses (wall shear stress and turbulent stress) cannot be readily addressed with current experimental techniques. Therefore, a numerical simulation procedure for flow through artificial heart valves is presented. The algorithm employed is based on the Navier-Stokes equations in generalized curvilinear coordinates with artificial compressibility for coupling of velocity and pressure. The algorithm applies a finite-difference technique on a body-conforming composite grid around the heart valve disk on which the numerical simulations are performed. Steady laminar flow over a backward-facing step and unsteady laminar flow inside a square driven cavity are computed to validate the algorithm. Two-dimensional, time-accurate simulation of flow through a tilting disk valve with a steady upstream Reynolds number as high as 1000 reveals the complex behavior of 'vortex shedding'. By scaling the results at the Reynolds number of 1000 to peak systolic flow conditions, the maximum value of shear stress on the valve disk is estimated to be 770 dyn cm-2. The 'apparent' Reynolds stress associated with vortex shedding is estimated to be as high as 3900 dyn cm-2 with a vortex shedding frequency of about 26 Hz. The 'apparent' Reynolds stress value is of similar magnitude as reported in experiments but would not be expected to damage blood cells because the spatial scales associated with vortex shedding are much larger than blood cell dimensions.

Algorithms↗
PubMed2004

Clinical validation of different echocardiographic motion pictures expert group-4 algorythms and compression levels for telemedicine.

Tele-echocardiography is not widely used because of lengthy transmission times when using standard Motion Pictures Expert Groups (MPEG)-2 lossy compression algorythms, unless expensive high bandwidth lines are used. We sought to validate the newer MPEG-4 algorythms to allow further reduction in echocardiographic motion video file size. Four cardiologists expert in echocardiography read blindly 165 randomized uncompressed and compressed 2D and color Doppler normal and pathologic motion images. One Digital Video and 3 MPEG-4 compression algorythms were tested, the latter at 3 decreasing compression quality levels (100%, 65% and 40%). Mean diagnostic and image quality scores were computed for each file and compared across the 3 compression levels using uncompressed files as controls. File dimensions decreased from a range of uncompressed 12-83 MB to MPEG-4 0.03-2.3 MB. All algorythms showed mean scores that were not significantly different from uncompressed source, except the MPEG-4 DivX algorythm at the highest selected compression (40%, p=.002). These data support the use of MPEG-4 compression to reduce echocardiographic motion image size for transmission purposes, allowing cost reduction through use of low bandwidth lines.

Algorithms↗