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Image compression in digital mammography: effects on computerized detection of subtle microcalcifications.

Our previous receiver operating characteristic (ROC) study indicated that the detection accuracy of microcalcifications by radiologists is significantly reduced if mammograms are digitized at 0.1 mm x 0.1 mm. Our recent study also showed that detection accuracy by computer decreases as the pixel size increases from 0.035 mm x 0.035 mm. It is evident that very large matrix sizes have to be used for digitizing mammograms in order to preserve the information in the image. Efficient compression techniques will be needed to facilitate communication and archiving of digital mammograms. In this study, we evaluated two compression techniques: full frame discrete cosine transform (DCT) with entropy coding and Laplacian pyramid hierarchical coding (LPHC). The dependence of their efficiency on the compression parameters was investigated. The techniques were compared in terms of the trade-off between the bit rate and the detection accuracy of subtle microcalcifications by an automated detection algorithm. The mean-square errors in the reconstructed images were determined and the visual quality of the error images was examined. It was found that with the LPHC method, the highest compression ratio achieved without a significant degradation in the detectability was 3.6:1. The full frame DCT method with entropy coding provided a higher compression efficiency of 9.6:1 at comparable detection accuracy. The mean-square errors did not correlate with the detection accuracy of the microcalcifications. This study demonstrated the importance of determining the quality of the decompressed images by the specific requirements of the task for which the decompressed images are to be used. Further investigation is needed for selection of optimal compression technique for digital mammograms.

Breast Diseases↗

New adaptive color quantization method based on self-organizing maps.

Color quantization (CQ) is an image processing task popularly used to convert true color images to palletized images for limited color display devices. To minimize the contouring artifacts introduced by the reduction of colors, a new competitive learning (CL) based scheme called the frequency sensitive self-organizing maps (FS-SOMs) is proposed to optimize the color palette design for CQ. FS-SOM harmonically blends the neighborhood adaptation of the well-known self-organizing maps (SOMs) with the neuron dependent frequency sensitive learning model, the global butterfly permutation sequence for input randomization, and the reinitialization of dead neurons to harness effective utilization of neurons. The net effect is an improvement in adaptation, a well-ordered color palette, and the alleviation of underutilization problem, which is the main cause of visually perceivable artifacts of CQ. Extensive simulations have been performed to analyze and compare the learning behavior and performance of FS-SOM against other vector quantization (VQ) algorithms. The results show that the proposed FS-SOM outperforms classical CL, Linde, Buzo, and Gray (LBG), and SOM algorithms. More importantly, FS-SOM achieves its superiority in reconstruction quality and topological ordering with a much greater robustness against variations in network parameters than the current art SOM algorithm for CQ. A most significant bit (MSB) biased encoding scheme is also introduced to reduce the number of parallel processing units. By mapping the pixel values as sign-magnitude numbers and biasing the magnitudes according to their sign bits, eight lattice points in the color space are condensed into one common point density function. Consequently, the same processing element can be used to map several color clusters and the entire FS-SOM network can be substantially scaled down without severely scarifying the quality of the displayed image. The drawback of this encoding scheme is the additional storage overhead, which can be cut down by leveraging on existing encoder in an overall lossy compression scheme.

Algorithms↗

Algorithms for the computation of solutions of the Ornstein-Zernike equation.

We introduce a robust and efficient methodology to solve the Ornstein-Zernike integral equation using the pseudoarc length (PAL) continuation method that reformulates the integral equation in an equivalent but nonstandard form. This enables the computation of solutions in regions where the compressibility experiences large changes or where the existence of multiple solutions and so-called branch points prevents Newton's method from converging. We illustrate the use of the algorithm with a difficult problem that arises in the numerical solution of integral equations, namely the evaluation of the so-called no-solution line of the Ornstein-Zernike hypernetted chain (HNC) integral equation for the Lennard-Jones potential. We are able to use the PAL algorithm to solve the integral equation along this line and to connect physical and nonphysical solution branches (both isotherms and isochores) where appropriate. We also show that PAL continuation can compute solutions within the no-solution region that cannot be computed when Newton and Picard methods are applied directly to the integral equation. While many solutions that we find are new, some correspond to states with negative compressibility and consequently are not physical.

Journal Article↗

Seamless multiresolution display of portable wavelet-compressed images.

Image storage, display, and distribution have been difficult problems in radiology for many years. As improvements in technology have changed the nature of the storage and display media, demand for image portability, faster image acquisition, and flexible image distribution is driving the development of responsive systems. Technology, such as the wavelet-based multiresolution seamless image database (MrSID) portable image format (PIF), is enabling image management solutions that address the shifting "point-of-care." The MrSID PIF employs seamless, multiresolution technology, which allows the viewer to determine the size of the image to be viewed, as well as the position of the viewing area within the image dataset. In addition the MrSID PIF allows control of the compression ratio of decompressed images. This capability offers the advantage of very rapid image recall from storage devices and portability for rapid transmission and distribution using the internet or wide-area networks. For example, in teleradiology, the radiologist or other physician desiring to view images at a remote location has full flexibility in being able to choose a quick display of an overview image, a complete display of a full diagnostic quality image, or both without compromising communication bandwidth. The MrSID algorithm will satisfy Joint Photographic Experts Group (JPEG) 2000 standards, thereby being compatible with future versions of the Digital Imaging and Communications in Medicine (DICOM) standard for image data compression.

Algorithms↗

Algorithms to analyze ventricular fibrillation signals.

Prediction of the success of defibrillation to avoid myocardial injury and performance feedback during CPR requires algorithms to analyze ventricular fibrillation signals. This report reviews investigations on different parameters of ventricular fibrillation electrocardiographic signals, including amplitude, frequency, bispectral analysis, amplitude spectrum area, wavelets, nonlinear dynamics, N(alpha) histograms, and combinations of several of these parameters. To date, no satisfactory methods have been found that cope with CPR artifacts and show adequate predictive power of successful defibrillation. The usual limitations of the studies are the small number of subjects, which precludes separation into training and test data. Because many investigations are animal studies of untreated short ventricular fibrillation, the results may be different for prolonged ventricular fibrillation in humans. The universality of threshold values has to be examined, and promising new parameters have to be monitored over longer time periods and analyzed for the effects of chest compressions, ventilation, and concomitant vasopressor therapy.

Algorithms↗

Abdominal wall pain: an alternative diagnosis.

The cause of abdominal pain need not necessarily reside in the viscera; the abdominal wall is another source of symptoms. Some causes of abdominal wall pain are obvious, e.g. hernias, but not so others such as nerve entrapment syndromes. This review is concerned with causes of abdominal wall pain which, although common, may be easily overlooked.

Abdominal Muscles↗

Image analysis techniques for automatic evaluation of two-dimensional electrophoresis.

Techniques for automatic analysis of two-dimensional electrophoresis gels by computer-aided image analysis are described. Original gels or photographic films are scanned using a laser scanner and the files are transferred to a microcomputer. The program package first performs a compression and preevaluation of the files. Spot identification and quantification is performed by the chain code algorithm after appropriate zooming and cutting. Labeling facilitates spot identification and quantification in numerical and graphical (pseudocolor) representation on peripheral devices for camera ready output. Interpolation between measured basepoints is performed by cubic spline algorithms which are automatically switched on and off, depending on the need by the program. High speed analysis and graphic representation is achieved using fast Assembler language routines rather than high level languages. One-dimensional gels can be analyzed using the same software. Spot matching between parallel two-dimensional gels has not yet been implemented.

Electrophoresis, Gel, Two-Dimensional↗

An inverse dynamics modeling approach to determine the restraining function of human knee ligament bundles.

During knee motion, the fiber bundles of ligaments are nonuniformly loaded in a recruitment pattern which is different for successive knee-joint positions. As a result, the restraining functions of these ligaments are variable. To analyze the relative restraint contributions of the fiber bundles in different knee-joint positions, a new method was developed. Its application was illustrated for the cruciate ligaments of one knee-joint specimen. The methods developed to estimate bundle forces comprise five steps. First, the three-dimensional motions of a knee specimen are measured for anterior-posterior forces, using Röntgen Stereophotogrammetric Analysis. Second, bone-ligament-bone tensile tests are performed to evaluate the mechanical properties of these structures in several relative orientations of the bones. Third, multiple fiber bundles are identified in each ligament, based on the main fiber orientations. Fourth, the nonlinear force-length relationship of each functional bundle, as defined by a stiffness and a recruitment parameter, is determined by combining the multidirectional tensile tests with a multiline-element ligament model. Finally, the information obtained is combined in a whole-joint computer model of the knee, to determine the internal forces in the initial kinematic experiment, using an inverse dynamics approach. The technique appeared to be extremely time consuming and technologically involved. However, it was demonstrated to be useful and effective. The preliminary results reveal that the fiber bundle restraints are extremely sensitive to the knee flexion angle and the restraining forces are highly variable within the ligaments. For both cruciate ligaments, a gradual transition was demonstrated in load transfer from the posterior bundles to the more anteriorly positioned ones during knee flexion. Furthermore, it appeared that relatively high forces were carried by only a few fiber bundles at each flexion angle. Based on these preliminary results, it is concluded that the determination of forces in multiple ligament bundles is important for the understanding of failure mechanisms of ligaments. In particular, alternate loading of different fiber bundles suggests that successful operative reconstruction of the cruciate ligaments may not be achieved simply by a one-bundle preparation.

Algorithms↗

The diagnosis of lower extremity deep venous thrombosis.

The diagnosis of lower extremity deep venous thrombosis (DVT) is critical to emergency physicians because of the risk of pulmonary embolism. This article reviews the diagnostic modalities available for patients with suspected lower extremity DVT. The use of compression ultrasonography and the recent advances in the D-dimer assays are emphasized. A clinical algorithm that utilizes a non invasive approach to this potentially life threatening disease is presented.

Algorithms↗

Biped walking robots created at Waseda University: WL and WABIAN family.

This paper proposes the mechanism and control of the biped humanoid robots WABIAN-RIV and WL-16. WABIAN-RIV has 43 mechanical degrees of freedom (d.f.): 6 d.f. in each leg, 7 d.f. in each arm, 3 d.f. in each hand, 2 d.f. in each eye, 4 d.f. in the neck and 3 d.f. in the waist. Its height is about 1.89 m and its total weight is 127 kg. It has a vision system and a voice recognition system to mimic some of the capabilities of the human senses. WL-16 consists of a pelvis and two legs having six 1 d.f. active linear actuators. An aluminium chair is mounted on two sets of its telescopic poles. To reduce the large support forces during the support phase, a support torque reduction mechanism is developed, which is composed of two compression gas springs with different stiffness. For the stability of the robots, a compensatory motion control algorithm is developed. This control compensates for moments generated by the motion of the lower limbs, using the motion of the trunk and the waist that is obtained by the zero moment point concept and fast Fourier transform. WABIAN-RIV is able to walk forwards, backwards and sideways, dance, carry heavy goods and express emotion, etc. WL-16 can move forwards, backwards and sideways while carrying an adult weighing up to 60 kg.

Artificial Intelligence↗

Automatic 3-d modeling of textured cultural heritage objects.

A widespread use of three-dimensional (3-D) models in cultural heritage application requires low cost equipment and technically simple modeling procedures. In this context, methods for automatic 3-D modeling of textured objects will play a central role. Such methods need fully automatic techniques for 3-D views registration and for the removal of texture artifacts. This paper proposes a contribution in this direction based on image processing approaches. The proposed procedure is very robust and simple. It does not require special equipment or skill in order to make textured 3-D models. The results of this paper, originally conceived to address the costs issues of cultural heritage modeling, can be profitably exploited also in other modeling applications.

Algorithms↗

Fast-searching algorithm for vector quantization using projection and triangular inequality.

In this paper, a new and fast-searching algorithm for vector quantization is presented. Two inequalities, one used for terminating the searching process and the other used to delete impossible codewords, are presented to reduce the distortion computations. Our algorithm makes use of a vector's features (mean value, edge strength, and texture strength) to reject many unlikely codewords that cannot be rejected by other available approaches. Experimental results show that our algorithm is superior to other algorithms in terms of computing time and the number of distortion calculations. Compared with available approaches, our method can reduce the computing time and the number of distortion computations significantly. Compared with the best method of reducing distortion computation, our algorithm can further reduce the number of distortion calculations by 29% to 58.4%. Compared with the best encoding algorithm for vector quantization, our approach also further reduces the computing time by 8% to 47.7%.

Algorithms↗

Demosaicing by successive approximation.

In this paper, we present a fast and high-performance algorithm for color filter array (CFA) demosaicing. CFA demosaicing is formulated as a problem of reconstructing correlated signals from their downsampled versions with an opposite phase. The major contributions of this work include (1) a new iterative demosaicing algorithm in the color difference domain and (2) a spatially adaptive stopping criterion for suppressing color misregistration and zipper artifacts in the demosaiced images. We have compared the proposed demosaicing algorithm with two current state-of-the-art techniques reported in the literature. Ours outperforms both of them on demosaicing performance and computational cost.

Algorithms↗

Weighted unequal error protection for transmitting scalable object-oriented images over packet-erasure networks.

In this paper, we investigate the problem of transmitting embedded encoded object-oriented images over the packet-erasure networks. After giving a review of the existing combined unequal error protection (CUEP) and individual unequal error protection (IUEP) schemes, a novel weighted unequal error protection (WUEP) packetization scheme is proposed, which serves as an alternative to the existing methods. In our proposed framework, the embedded bitstreams of all concerned image objects are packetized into multiple description packet streams before transmission. Two levels of rate allocation are introduced: intraobject rate allocation provides unequal error protection to the embedded bitstream of each object and minimizes its associated mean distortion; interobject rate allocation aims at minimizing the weighted mean distortion by adaptively allocating the rate budget among different objects according to their importance. Furthermore, our proposed packetization scheme ensures independent access and manipulation of individual image object. A detailed comparison between CUEP, IUEP, and WUEP is presented along with the experimental results, so that one can choose the most suitable approach according to the requirements.

Algorithms↗

The eidochromatic transform for color-image coding.

We introduce the eidochromatic transform as a tool for improved lossy coding of color images. Many current image-coding formats (such as JPEG 2000) utilize both a color-component transform (relating values of different image components at a single location) and a wavelet or other spatial transform (relating values of a single-image component at proximate, but different image locations). The eidochromatic transform further reduces redundancy by relating image values simultaneously across color components and in the two spatial dimensions. Our approach is to introduce an additional transform step following the color-component and spatial transforms. In tests, this step reduced the overall static entropy of the chrominance components of quantized transformed images by up to 40% or more. Combined with JPEG 2000's modeling and coding method, the eidochromatic transform was found to reduce the size of lossily coded color images by up to 27% overall.

Algorithms↗

Multipurpose image watermarking algorithm based on multistage vector quantization.

The rapid growth of digital multimedia and Internet technologies has made copyright protection, copy protection, and integrity verification three important issues in the digital world. To solve these problems, the digital watermarking technique has been presented and widely researched. Traditional watermarking algorithms are mostly based on discrete transform domains, such as the discrete cosine transform, discrete Fourier transform (DFT), and discrete wavelet transform (DWT). Most of these algorithms are good for only one purpose. Recently, some multipurpose digital watermarking methods have been presented, which can achieve the goal of content authentication and copyright protection simultaneously. However, they are based on DWT or DFT. Lately, several robust watermarking schemes based on vector quantization (VQ) have been presented, but they can only be used for copyright protection. In this paper, we present a novel multipurpose digital image watermarking method based on the multistage vector quantizer structure, which can be applied to image authentication and copyright protection. In the proposed method, the semi-fragile watermark and the robust watermark are embedded in different VQ stages using different techniques, and both of them can be extracted without the original image. Simulation results demonstrate the effectiveness of our algorithm in terms of robustness and fragility.

Algorithms↗

Ergodic chaotic parameter modulation with application to digital image watermarking.

This paper presents a novel technique for image watermarking based on chaos theory. Chaotic parameter modulation (CPM) is employed to modulate the copyright information into the bifurcating parameter of a chaotic system. The system output is a wideband signal and is used as a watermark to be inserted into the host image. In the detection, a novel method based on the ergodic property of chaotic signal is developed to demodulate the embedded copyright information. Compared to previous works on blind watermarking, the proposed technique can effectively remove the interference from the host image and, thus, improve the detection performance dramatically. Simulation results show that the ergodic CPM approach is effective for image watermarking in terms of noise performance, robustness against attacks, and payload. In addition, its implementation is very simple and the computation speed is fast. Compared to holographic transform domain method and the conventional spread spectrum watermarking scheme, the proposed technique is shown to be superior.

Algorithms↗