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A gamma-camera on-line distortion corrector, based on a fast microprocessor, has been tested on two cameras. The original electronic design and the software algorithm are described. Performance measurements on phantoms and clinical results show an improvement of the pictures.
Classification of opacities in pneumoconiosis was accomplished by textural analysis in digitised chest x-rays. A good discrimination was achieved by a set of 10 parameters. These texture measures were computed by algorithms for edge detection, local extremes, difference statistics, the co-occurrence matrix and the power spectrum. The classes of the training set were classified correctly at 99%. A test set comprising additional classes that were not contained in the training set, was classified at 82%.
Recent progress in electrical impedance tomography in North America is reviewed. It emphasises recent progress on the hardware system, measurement method, and reconstruction algorithm. It also describes two new EIT applications.
We have previously developed a general method based on the statistical technique of discriminant analysis to predict splice junctions in eukaryotic mRNA sequences [Nakata, K., Kanehisa, M. and DeLisi, C. (1985) Nucleic Acids Res., 13, 5327-5340]. In order to evaluate further applicability of this method, we now analyze the promoter region of Escherichia coli sequences. The attributes used for discrimination include the accuracy of consensus sequence patterns measured by the perceptron algorithm, the thermal stability map, the base composition and the Calladine-Dickerson rules for helical twist angle, roll angle, torsion angle and propeller twist angle. When applied to selected E. coli sequences in the GenBank database, the method correctly identifies 75% of the true promoter regions.
The diagnostic performance of two pattern recognition methods (or classifiers) to detect valvular degeneration was evaluated in 48 patients with a porcine bioprosthetic heart valve inserted in the mitral position. Twenty patients had a normal porcine bioprosthetic valve and 28 patients had a degenerated bioprosthetic valve. One method was based on the Gaussian-Bayes model and the second on the "nearest neighbor" algorithm using three distance measurements. Eighteen diagnostic features were extracted from the sound spectrum of each patient and, for each method, a two-class supervised learning approach was used to determine the most discriminant diagnostic patterns composed of 6 features or less. The probability of error of the classifiers was estimated with the leave-one-out approach. The performance of each method to discriminate between normal and degenerated bioprosthetic valves was verified by clinical evaluation of the valves. The best performance in evaluation of the sound spectrum (98% correct classifications) was obtained with the Bayes classifier and two patterns of six features each. The percentage of false positive classifications of valve degeneration was 0% and the percentage of false negative classifications was 4%. Sensitivity for the detection of valve degeneration was 96%, specificity was 100%, positive predictive value was 100%, and negative predictive value was 95%. The best performance of the nearest neighbor method (94% correct classifications) was obtained by using the Mahalanobis distance and five patterns composed of three, four, five, or six diagnostic features. Using a pattern composed of only three features, the percentage of false positive classifications for degeneration was 10% and the percentage of false negative classifications was 4%.(ABSTRACT TRUNCATED AT 250 WORDS)
An overall approach to evaluating and treating ventricular arrhythmias based on objective monitoring criteria is described. A clinically useful system classifies patients based on whether their ventricular arrhythmias are benign, potentially lethal, or lethal. Some clinicians believe that antiarrhythmic drug therapy improves survival in patients with potentially lethal arrhythmias. However, disappointing results from the Cardiac Arrhythmia Suppression Trial have led to a greater awareness of the potential adverse effects of antiarrhythmics. Various risk factors for arrhythmia-related death have been identified, such as the presence of frequent and complex ventricular ectopy, abnormal signal-averaged electrocardiography (SAECG) tracings, and poor left ventricular ejection fraction (LVEF). Antiarrhythmic drugs remain the primary mode of therapy for patients with recurrent symptomatic tachycardias. Antiarrhythmic drug efficacy has been evaluated by methods including symptom assessment, continuous ambulatory electrocardiographic monitoring (Holter monitoring), exercise testing, and invasive electrophysiologic testing. There may be an extremely wide range of effective serum concentrations for the class IA agents. Individual target concentrations of antiarrhythmic agents may be determined for individual patients and should assist the clinician in optimizing long-term antiarrhythmic drug therapy. The risk-to-benefit ratio of treatment should be weighed before antiarrhythmic drug therapy is begun, and careful, objective monitoring of drug efficacy should be performed. When pharmacologic treatment of ventricular arrhythmias is considered, treatment algorithms that incorporate LVEF measurements, Holter monitor recordings, and SAECG may aid the clinician.
A recently developed program for the irradiation planning of intracavitary afterloading applications in the treatment of gynecological diseases is presented. On the basis of measured data, a rapid algorithm for calculating the dose within the field near to ray emitters is introduced which avoids any uncertainties as to the greatest activity and the dose rate constant. Distance- and direction-dependent corrections of the inverse square law are performed by means of polynomials easy to calculate or by tables. The structure and performance of the program are described. Some examples are given in order to illustrate the possible applications of the irradiation planning program.
The results of combined radiodiagnosis of the urinary system in patients with renal tumors before and after nephrectomy were analyzed. Investigations included excretory urography and renography with the processing of the results of measurements by a common algorithm and on the basis of 3 mathematical models of RP body transport. The results were correlated with the findings of biochemical blood and urine tests and pathoanatomical investigation of the removed kidney. Ample potentialities of renography for the detection of latent renal insufficiency in the preoperative period and for accurate and exhaustive assessment of function of the urinary system were shown.
The task was to develop a simple and effective method of radionuclide determination of separate clearance of the kidneys (SCK), i.e. separate assessment of secretory-excretory function of each kidney. The other earlier known methods of SCK determination were either methodologically incorrect or very difficult. A method of SCK determination intended both for gamma-chambers and standard radiographic units based on common renographic methods, was proposed. An algorithm for processing of measurement results was based on the generalization of the mathematical apparatus of circulation models usually employed for a study of the central and organ hemodynamics, and on its development for transitory nephrotropic radiopharmaceuticals (RP). An investigation of 21 healthy persons and 51 patients with renal tumors using 131I-hippuran showed that the proposed method possessed sufficient sensitivity for its clinical use. Advantages and shortcomings of the method were analysed. All the allowances were justifiable.
The absorption profile of the distal forearm, which depends on bone mineralisation, was measured using a high resolution microcomputer-controlled transverse rotational scanner with a tightly collimated I-125 photon source and a scintillation counter. Reconstruction of the anatomical structures within the measured area occurred in two stages. Subsequently the linear attenuation coefficient for soft tissues, compacta and spongiosa was obtained by a "least-square" algorithm. The absorption coefficient of the compacta and spongiosa provided a measure of bone mineralisation. Correlation between the reconstructed images and the calculated results and measurements was tested by calculation. Ten measurements of a model and of in vivo bones resulted in a coefficient of variation of 1.8% and 3.3% for the compacta and 2.5% and 3.8% for the spongiosa. Relative deviation from the standard varied from +1.3% to -1.0%, depending on mineral content. This new, technically simple procedure for the separate determination of the compacta and spongiosa in the distal radius is useful for the early recognition of changes in bone mineralisation which are usually apparent first in the spongiosa.
We have developed a three-dimensional, computer-simulated, electrical impedance tomographic imaging system using the four-electrode measurement technique. The reconstruction process finds the numerical solution of Laplace's equation by using the finite element method and the Newton-Raphson algorithm. A new diagonal electrodes measurement method provides lower error than the usual neighbouring electrodes measurement method. For a three-layer, 4 x 4 model, the number of iterations increased from 3 to 16 as the number of randomly placed, high-resistivity voxels increased from 3 to 18.
A computer program may be capable of several different statements for left ventricular hypertrophy (eg, possible LVH, probable LVH, consistent with LVH), but such statements resulting from discretized levels of sensitivity/specificity would represent only isolated points on a receiver-operating characteristic (ROC) curve, which is a plot of all levels of sensitivity versus specificity. Even if two algorithms use the same discrete scales, their performances may not readily be compared. The authors present a comparison methodology for ROC curves using ROC area as a nonparametric measure of the ability of the algorithm to separate the two populations; the ROC area ranges from 0.5 (no ability) to 1.0 (perfect separation) and is unbiased if the normal versus abnormal populations have no common values for the measurement. The methodology compares the performance of ECG algorithms on the same population of cases by testing for significant differences of ROC areas and incorporating correlation of the algorithms in a nonparametric way. To illustrate this methodology, they use ECG and echocardiographic data from the Framingham Heart Study.
A new method to measure the dynamic range of electrotactile (electrocutaneous) stimulation uses both steepest ascent (gradient) and one-variable-at-a-time methods to determine the waveform variables that maximize the subjective magnitude (intensity) of the electrotactile percept at the maximal current without discomfort for balanced-biphasic pulse bursts presented at a 15-Hz rate. The magnitude at the maximal current without discomfort is maximized by the following waveform (range tested in parentheses): number of pulses/burst = 6 (1-20), pulse repetition rate within a burst = 350 Hz (200-1500), and phase width = 150 microseconds (40-350). The interphase interval (separation between positive and negative phases in a biphasic pulse) does not affect dynamic range from 0-500 microseconds. The number of pulses/burst has a large effect on the perceived dynamic range when this is measured using a subjective-magnitude-based algorithm, whereas it has little effect on the traditional dynamic range measure, i.e., (maximal current without discomfort)/(sensation threshold current). The perceived stimulus magnitude at the maximal current without discomfort is approximately twice as strong with 6 pulses/burst as it is with 1 pulse/burst (a frequently-used waveform).
In order to circumvent the electrode position determination problem in static electrical impedance tomography, it is possible to insert the object to be imaged into a water-filled cylinder on which the electrodes are at fixed and known positions. It has previously been shown that if the boundary of the internally placed object and the conductivity of the salty water in the cylinder are known, then a significant improvement in the conductivity image of the object is obtained. An algorithm for finding the boundary of an internally placed object is developed based on the finite element method (FEM). The boundary is assumed to obey a parametric model and the parameters are estimated by inverting a matrix representing the sensitivity of the boundary voltage measurements to parameter variations. The algorithm assumes that the object's internal conductivity is uniform and known. Simulation studies show that if the internal conductivity is not uniform to the extent found in the arm cross-sections, up to 9% error in the boundary, as measured from a centrally placed reference point, may result. It is also shown that if previous knowledge about the boundary shape is used to model the boundary with fewer numbers of parameters, then the boundary may be found with less error.
The application of dual energy (DE) subtraction techniques to quantitative coronary arteriography (QCA) has the advantage of removing the tissue signal surrounding the vessel profile. We have compared the performance of two geometric QCA algorithms on DE-subtracted and -unsubtracted images to determine, for each, if DE subtraction is advantageous. The two algorithms under study were an edge detection algorithm and a Fourier analysis-based algorithm. For each algorithm, linear regression analysis was performed of measured cross-sectional area (CSA) versus actual CSA of coronary vessel phantoms. The edge detection algorithm was found to have improved precision (P less than .05) when applied to the DE-subtracted images. The Fourier analysis algorithm, however, was not effected by the DE subtraction. Among the unsubtracted image results, the Fourier measurements were more accurate (P less than .05) than the edge detection measurements. We conclude that the benefits to edge detection QCA of DE tissue subtraction outweigh the disadvantages of increased image noise and possible misregistration artifacts. However, the Fourier algorithm is relatively insensitive to tissue signal variations.
We describe a computer algorithm for classifying serum monoclonal proteins (MC) based on serum protein electrophoresis (SPE) and the automated measurement of kappa and lambda light chains and IgG, IgA, and IgM. We developed the algorithm by using a large database of unselected samples containing MC collected in a multicenter study. The performance of the algorithm was optimized by using iterative computational procedures and was tested on both the development database and on an independent set of MC-containing samples. With the development database, the algorithm correctly classified 50% and misassigned 2.5% of the MC. Where the MC were present in concentrations greater than 10 g/L, the rate of successful classification increased to 72% with 3% misclassification. When the algorithm was tested on a group of 101 MC-containing samples from an independent source, 67% were correctly classified and 8% misclassified, half of the latter being unusual IgD myelomas. We discuss the scope for the application of the algorithm in routine laboratory practice involving personal computer software.
Quantitative histological methods have proved to be the most effective methods in bone disease research. Faster and more accurate techniques are currently needed. We have developed a simple digitized image analysis system which allows accurate measurements of trabecular bone mass. The algorithm is based on the 'four-connected sets' mathematical theory. Given a numerized image displayed by a CCD camera, the algorithm recognizes all possible four-connected sets and provides area measurements. The first procedure automatically eliminates small, irrelevant profiles (wrinkles, cell nuclei, etc.) while larger profiles are erased interactively. The second procedure similarly erases the artefactual defects within the trabeculae (artefactual cracks or empty osteocytic lacunae). The method was shown to be very accurate and time-saving.
Four classification algorithms based on Bayes' rule for minimum error are compared by evaluating their ability to recognize high- and normal-risk cardio-surgical patients. These algorithms differ in the modelling of the probability density function (pdf) for each class and include: (a) two parametric algorithms based on the assumption of normal pdf; (b) two non-parametric algorithms using Parzen multidimensional approximation of pdf with normal kernels. In each case, classes with both equal and different covariance matrices were considered. A set of 200 patients in the 6 h immediately following cardiac surgery has been used to test the performance of the algorithms. For each patient the three measured variables most effective in representing the difference between the two classes were considered. We found that the two algorithms which explicitly incorporate the information on the different sample covariance between the physiological variables existing in the two classes generally provide better recognition of high- and normal-risk patients. Of these two algorithms the parametric one appears extremely attractive for practical applications, since it exhibits slightly better performance in spite of its great simplicity.