SEARCH · Search PubMed
Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A fast technique for implementing Holter cardio real time data reduction based on pointer and dual data buffers is presented in this paper, and an example of its application is also given here.
Depending on the purpose for which a medical image is taken, some areas of it contain more clinical information than others. These areas are usually considered as regions of interest (ROI). The area outside the ROI is either the background or contains some clinical information with relative importance. In this paper we introduce two preprocessing and error-free compression routines. The first preprocessing routine, if applied to X-ray images, could result in a reconstructed image with a controllable amount of deterioration in its various areas. The second preprocessing routine is applied to X-ray CT, MR and radionuclide images prior to the compression. Its aim is to automatically detect the ROI and neglect the background. The background is replaced by an optional gray level when these images are being reconstructed. These routines were applied to a variety of medical images and relatively good compression ratios were obtained.
Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.
As our knowledge of biological processes advances, we are increasingly aware that cells actively position sub-cellular organelles and other constituents to control a wide range of biological processes. Many studies quantify the position and motion of, for example, fluorescently labeled proteins, protein aggregates, mRNA particles or virus particles. Both differential interference contrast (DIC) and fluorescence microscopy can visualize vesicles, nuclei or other small organelles moving inside cells. While such studies are increasingly important, there has been no complete analysis of the different tracking methods in use, especially from the practical point of view. Here we investigate these methods and clarify how well different algorithms work and also which factors play a role in assessing how accurately the position of an object can be determined. Specifically, we consider how ultimate performance is affected by magnification, by camera type (analog versus digital), by recording medium (VHS and SVHS tape versus direct tracking from camera), by image compression, by type of imaging used (fluorescence versus DIC images) and by a variety of sources of noise. We show that most methods are capable of nanometer scale accuracy under realistic conditions; tracking accuracy decreases with increasing noise. Surprisingly, accuracy is found to be insensitive to the numerical aperture, but, as expected, it scales with magnification, with higher magnification yielding improved accuracy (within limits of signal-to-noise). When noise is present at reasonable levels, the effect of image compression is in most cases small. Finally, we provide a free, robust implementation of a tracking algorithm that is easily downloaded and installed.
RATIONALE AND OBJECTIVES: The authors investigated the diagnostic efficacy of compression of real-time ultrasound (US) examinations. METHODS: Low- and high-compression recordings (9:1 and 15:1, respectively) of examinations were generated by using Joint Photographic Experts Group algorithms. Seven radiologists used a five-level response scale to answer questions about the presence, number, and location of focal fibroid tumors in 67 randomly sorted uterine examinations. The images were viewed after no, low, and high compression. Results were evaluated by using multipatient, multireader receiver operating characteristic jack-knife analysis. RESULTS: Given the reduction in the US digital video rates from 74 Mbit/sec for uncompressed images to 8 Mbit/sec for low compression and 4.7 Mbit/sec for high compression, there were no statistically significant differences in accuracy between the compression schemes. Confidence intervals suggested that the sample size was adequate. CONCLUSION: Compressed images with compression ratios of 9:1 and 15:1 were diagnostically equivalent to uncompressed images of uterine fibroid tumors.
We present a computationally efficient and numerically robust solution to the problem of removing artifacts due to precordial compressions and ventilations from the human electrocardiogram (ECG) in an emergency medicine setting. Incorporated into automated external defibrillators, this would allow for simultaneous ECG signal analysis and administration of precordial compressions and ventilations, resulting in significant clinical improvement to the treatment of cardiac arrest patients. While we have previously demonstrated the feasibility of such artifact removal using a multichannel Wiener filter, we here focus on an efficient matching pursuit-like approach making practical real-time implementations of such a scheme feasible for a wide variety of sampling rates and filter lengths. Using more realistic data than what have been previously available, we present evidence showing the excellent performance of our approach and quantify its computational complexity.
Spatial resolution and contrast sensitivity requirements for some types of medical image techniques, including mammography, delay the implementation of new digital technologies, namely, computer-aided diagnosis, picture archiving and communications systems, or teleradiology. In order to reduce transmission time and storage cost, an efficient data-compression scheme to reduce digital data without significant degradation of medical image quality is needed. In this study, we have applied two region-based compression methods to digital mammograms. In both methods, after segmenting the breast region, a region-based discrete wavelet transform is applied, followed by an object-based extension of the set partitioning in hierarchical trees (OB-SPIHT) coding algorithm in one method, and an object-based extension of the set partitioned embedded block (OB-SPECK) coding algorithm in the other. We have compared these specific implementations against the original SPIHT and the new standard JPEG 2000, both using reversible and irreversible filters, on five digital mammograms compressed at rates ranging from 0.1 to 1.0 bit per pixel (bbp). Distortion was evaluated for all images and compression rates by the peak signal-to-noise ratio. For all images, OB-SPIHT and OB-SPECK performed substantially better than the traditional SPIHT and JPEG 2000, and a slight difference in performance was found between them. A comparison applying SPIHT and the standard JPEG 2000 to the same set of images with the background pixels fixed to zero was also carried out, obtaining similar implementation as region-based methods. For digital mammography, region-based compression methods represent an improvement in compression efficiency from full-image methods, also providing the possibility of encoding multiple regions of interest independently.
We present a computational model for periodic pattern perception based on the mathematical theory of crystallographic groups. In each N-dimensional Euclidean space, a finite number of symmetry groups can characterize the structures of an infinite variety of periodic patterns. In 2D space, there are seven frieze groups describing monochrome patterns that repeat along one direction and 17 wallpaper groups for patterns that repeat along two linearly independent directions to tile the plane. We develop a set of computer algorithms that "understand" a given periodic pattern by automatically finding its underlying lattice, identifying its symmetry group, and extracting its representative motifs. We also extend this computational model for near-periodic patterns using geometric AIC. Applications of such a computational model include pattern indexing, texture synthesis, image compression, and gait analysis.
Using two nonlinear finite element models of the lumbar spine, the concept of optimal posture is explored by minimizing the segmental sagittal moments required for the equilibrium of the passive lumbar spine under a total of 2800 N axial compression while varying the pelvic tilt and lumbar lordosis. The redundant active-passive system is subsequently solved for this posture using a novel kinematics-based muscle calculation algorithm along with minimization approach. Some flattening in the lumbar spine substantially reduces the required moments and internal passive shear forces under 2800 N axial compression force. Small muscle forces are calculated for this optimal posture. The role of flattening in the lumbar lordosis and posterior pelvic tilt in diminishing the lumbar muscle activities in neutral postures is demonstrated. Without such changes in posture, the required moments probably exceed the moment-generating capability of local lumbar muscles. Consideration of such active-passive synergy and lack of its restriction may prove crucial in many activities. Moreover, a kinematics-based algorithm is proposed for the solution of spinal redundancy that fully accounts for the existing passive-active synergy while simultaneously satisfying all kinematics and equilibrium conditions along the length of the spine.
Ultrasonic strain imaging has drawn much attention recently because of its ability to noninvasively provide information on spatial variation of the elastic properties of soft tissues. Traditionally, local strain is estimated by scaling and cross correlating pre- and postcompression ultrasound echo fields. However, when the motion field generated by compression is more complex, scaling and cross correlation can no longer provide precise displacement estimates because of signal decorrelation. We introduce a new algorithm based on the deformable mesh method. This algorithm can accommodate more general forms of motion, namely, the motion that can be described by bilinear transformations. We applied the new algorithm to three sets of data in order to evaluate its performance. In the first set of data, primitive motions such as shearing and rotation are simulated. The second set of data is collected by compressing a tissue-mimicking phantom with three hard inclusions. The third experiment involves an ex vivo pig kidney embedded in a block of gelatin. The results from all three experiments show improvements with the new algorithm over other methods.
Methods for discovery of local similarities and estimation of evolutionary distance by identifying k-mers (contiguous subsequences of length k) common to two sequences are described. Given unaligned sequences of length L, these methods have O(L) time complexity. The ability of compressed amino acid alphabets to extend these techniques to distantly related proteins was investigated. The performance of these algorithms was evaluated for different alphabets and choices of k using a test set of 1848 pairs of structurally alignable sequences selected from the FSSP database. Distance measures derived from k-mer counting were found to correlate well with percentage identity derived from sequence alignments. Compressed alphabets were seen to improve performance in local similarity discovery, but no evidence was found of improvements when applied to distance estimates. The performance of our local similarity discovery method was compared with the fast Fourier transform (FFT) used in MAFFT, which has O(L log L) time complexity. The method for achieving comparable coverage to FFT is revealed here, and is more than an order of magnitude faster. We suggest using k-mer distance for fast, approximate phylogenetic tree construction, and show that a speed improvement of more than three orders of magnitude can be achieved relative to standard distance methods, which require alignments.
Despite a general understanding that bone microdamage has distinct strain dependent morphologies, very little information exists on how different damage morphologies develop and participate in bone fracture. In this study, cortical bone beams were subjected to the primary or tertiary phases of bending fatigue followed by either post-hoc fracture toughness tests or microdamage analysis to determine the sequence in which linear microcracks and diffuse damage form during bending fatigue and how they affect the propensity of bone to fracture. The results demonstrate that, following the primary phase, linear microcracks and diffuse damage are formed on the compressive and tensile sides, respectively (p<0.05). Furthermore, this mode of damage formation results in a greater toughness loss if a fracture crack initiates from the tensile side rather than the compressive side (p<0.05). Continued loading of bone specimens to the tertiary phase, however, leads to further accumulation of damage only on the compressive side (p<0.05), and this mode of damage formation results in a further toughness loss if a fracture crack initiates from the compressive side rather than the tensile side (p<0.05). Thus, cortical bone compartmentalizes the damage morphologies in different regions and the sequence of damage production in different phases of cyclic loading to dissipate energy and resist a catastrophic fracture.
Growth plates are highly inhomogeneous in morphology and composition. Mechanical loading can modulate longitudinal bone growth, though the mechanisms underlying this mechanobiology are poorly understood. The proximal tibial growth plates of six rats were tested in vitro under uniaxial compression to 5% strain, and confocal microscopy was used to track and capture images of fluorescently labeled cell nuclei with increasing applied strains. The local strain patterns through the growth plate thickness were quantified using texture correlation analysis. The technique of texture correlation analysis was first validated by comparing theoretical simulated strain maps generated from numerically distorted images. The texture correlation algorithm was sensitive to the grid size superimposed on the original image, but remained insensitive to parameters related to the size of the final image mask, which was searched by the correlation algorithm for each grid point of the original image. Within the growth plate, experimental strain distributions were non-uniform in all six specimens. Growth plates were mostly under compression strains. The strain distributions differed among the histomorphological zones of the growth plate, which was most obvious in specimens with regular growth plate shape: higher compressive strains (4-8 times higher than the applied 5% strain) were located mainly in regions overlapping the reserve and hypertrophic zones with lower compressive strains in the proliferative zone. This study documents the non-uniform mechanical behavior of growth plate across its three histological zones when exposed to compression. Further investigation is required to establish the significance of non-uniform strain fields during growth in vivo.
For complex database prediction problems such as medical diagnosis, the ARTMAP-IC neural network adds distributed prediction and category instance counting to the basic fuzzy ARTMAP system. For the ARTMAP match tracking algorithm, which controls search following a predictive error, a new version facilitates prediction with sparse or inconsistent data. Compared to the original match tracking algorithm (MT+), the new algorithm (MT-) better approximates the real-time network differential equations and further compresses memory without loss of performance. Simulations examine predictive accuracy on four medical databases: Pima Indian diabetes, breast cancer, heart disease, and gall bladder removal. ARTMAP-IC results are equal to or better than those of logistic regression, K nearest neighbour (KNN), the ADAP preceptron, multisurface pattern separation, CLASSIT, instance-based (IBL), and C4. ARTMAP dynamics are fast, stable, and scalable. A voting strategy improves prediction by training the system several times on different orderings of an input set. Voting, instance counting, and distributed representations combine to form confidence estimates for competing predictions.
Penile incarceration is a rarely seen injury that requires urgent medical attention and may provide a challenge to even the most experienced emergency and urologic personnel. Described is a novel method of liberating the penis from a nonexpandable metal ring through a combination of multiple puncture wounds and manual compression after failure of other well-described techniques. Included is a treatment algorithm to guide progression of management options in difficult cases.
This paper proposes a method for progressive lossy-to-lossless compression of four-dimensional (4-D) medical images (sequences of volumetric images over time) by using a combination of three-dimensional (3-D) integer wavelet transform (IWT) and 3-D motion compensation. A 3-D extension of the set-partitioning in hierarchical trees (SPIHT) algorithm is employed for coding the wavelet coefficients. To effectively exploit the redundancy between consecutive 3-D images, the concepts of key and residual frames from video coding is used. A fast 3-D cube matching algorithm is employed to do motion estimation. The key and the residual volumes are then coded using 3-D IWT and the modified 3-D SPIHT. The experimental results presented in this paper show that our proposed compression scheme achieves better lossy and lossless compression performance on 4-D medical images when compared with JPEG-2000 and volumetric compression based on 3-D SPIHT.
The focus of this project is to improve our understanding of the relationships between brain structure and function in patients presenting with anterior visual pathway compression using functional MRI (fMRI), visual field(VF) maps and diffusion tensor imaging (DTI). Significant visual loss can occur when large pituitary lesions compress the optic chiasm. Surgical resection of these lesions decompresses the chiasm and can lead to visual recovery. In this preliminary study, we selected patients presenting with slowly progressive visual loss secondary to a compressive pituitary region mass. Using preoperative DTI data, we reconstructed white matter projections of the optic radiations and demonstrated a structural correlation with functional vision as quantified by formal visual field mapping and fMRI. The structural data generated through a fiber tracking algorithm may represent a potentially powerful tool to better understand functional visual deficits in patients with anterior visual pathway compression. Furthermore, we believe that specific patterns in preoperative DTI data may predict the likelihood of postoperative visual recovery in a select group of patients.
The computerized translation of "Handbook of glandular tissue doses in mammography" (HHS publication FDA 85-8239) is presented. It is registered on floppy disk and suitable for use in MS-DOS on IBM personal computer, Olivetti or compatible. The manual collects data published by many authors and suggests a method to estimate the dose released to the glandular tissue (considered at risk for breast cancer) in the most commonly used conditions for mammography. Besides translation manual, the program holds an algorithm developed by the authors, which allows the dose to the glandular tissue to be evaluated, given the following data: projection: craniocaudal or mediolateral; compression level: firm or moderate; breast size: small, medium or large; breast composition: percentage of glandular tissue content (by weight); X-ray beam quality: HVL mm Al. The algorithm is obtained from a bidimensional fit of the original data and is based on the terms contained in the manual. The program flow is guided by menus that make the procedure suitable for inexperienced operators too, both for consulting and printing and for computing program.