Thermal damage processes follow kinetic governing relations and resultant damage depends on both temperature and time of exposure. Application to models of cardiac ablation depends on identification of a quantitative ...
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Thermal damage processes follow kinetic governing relations and resultant damage depends on both temperature and time of exposure. Application to models of cardiac ablation depends on identification of a quantitative measure of thermal damage. Loss of the native state birefringence of myocardium is one such measure. Damage data derived from short term argon laser exposure and long term heated block experiments were adapted to model middle term heating as in cardiac ablation. Model predictions from the estimated coefficients compare favorably to the experimental observations; however, much remains to be learned about the true kinetic nature of the damage processes in this tissue.
A technique has been developed that allows the application of free-standing membranes of polymer adhesives used in microfabricated structures. The film is made free-standing by the application of the adhesive to a pol...
A technique has been developed that allows the application of free-standing membranes of polymer adhesives used in microfabricated structures. The film is made free-standing by the application of the adhesive to a polymer template, followed by an adhesion step to a microfabricated substrate, and the final release of the film by the removal of the polymer template. It was found that the surface treatment used to treat the Teflon template made it adhere too strongly to the adhesive film for this application. The results show that Gel-Paks make a suitable template for the transference of polymer films over holes of at least micron size.
We present the method of the elimination of ECG artifact from the polysomnographic EEG and EGG. The idea of this method is that the ECG-corrupted EEG segment can be detected from ECG R-wave and regarded as a missing s...
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We present the method of the elimination of ECG artifact from the polysomnographic EEG and EGG. The idea of this method is that the ECG-corrupted EEG segment can be detected from ECG R-wave and regarded as a missing segment. After this, we used two interpolations to recover the missing segment. One is the Lagrange polynomial interpolation and the other is the least square error AR interpolation. We also compared the AR-method with the LMS adaptive noise canceling method. Simulations show the AR-method performs better than other methods. To apply to the real EEG and EOG signals practically, we also developed the algorithm to detect whether the artifact level is high or not. If the artifact level is high, then the interpolations are applied.
Left ventricular relaxation time constant (/spl tau/) has been widely used in analysis of ventricular diastolic function. A new criterion to detect the ending point of isovolumic relaxation period (IRP) for the estima...
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Left ventricular relaxation time constant (/spl tau/) has been widely used in analysis of ventricular diastolic function. A new criterion to detect the ending point of isovolumic relaxation period (IRP) for the estimation of /spl tau/ in the left ventricular pressure waveform was developed. The proposed method is based on the pattern classification of mean square error between the original and the reconstructed pressure waveforms. We verified the performance of the new method using over 20,000 beats obtained from 96 patients. It showed that the proposed method provides more stable and accurate estimation results. The developed method is now being used in clinical application of real-time analysis of left ventricular diastolic function during cardiac catheterization procedure.
A computerized system composed of neurostimulator and EMG signal acquisition and real-time analysis system has been developed to be used for selective posterior rhizotomy. As a preliminary study for the clinical appli...
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A computerized system composed of neurostimulator and EMG signal acquisition and real-time analysis system has been developed to be used for selective posterior rhizotomy. As a preliminary study for the clinical application of the developed system, we performed a series of animal experiments using cats. From the results of in vivo application, we verified the basic system performance and found that latency, amplitude variance and waveform variance are useful parameters to differentiate sensory nerve from motor nerve. The underlying mechanisms of these phenomena were also provided. These findings were utilized in establishing the objective criterion in nerve selection for selective posterior rhizotomy.
For the objective interpretation of cerebral metabolic patterns in epilepsy patients, we developed a computer-aided classifier using artificial neural network. We studied interictal brain FDG PET scans of 257 epilepsy...
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For the objective interpretation of cerebral metabolic patterns in epilepsy patients, we developed a computer-aided classifier using artificial neural network. We studied interictal brain FDG PET scans of 257 epilepsy patients which were diagnosed as normal (n=64), left temporal lobe epilepsy (n=112), or right temporal robe epilepsy (n=81) by visual interpretation. Automatically segmented volumes of interest (VOI) were used to reliably extract the features representing patterns of cerebral metabolism. All images were spatially normalized to MNI standard PET template and smoothed with 16 mm FWHM Gaussian kernel using SPM96. Mean count in cerebral region was normalized. The VOI for 34 cerebral regions were previously defined on the standard template and 17 different counts of mirrored regions to hemispheric midline were extracted from spatially normalized images. A three-layer feedforward error backpropagation neural network classifier with 17 input nodes and 3 output nodes was used. The network was trained to interpret metabolic patterns and produce identical diagnoses with those of expert viewers. The performance of the neural network was optimized by testing with 5/spl sim/40 nodes in hidden layer. Randomly selected 40 images from each group were used to train the network and the remainders were used to test the learned network. The optimized neural network gave a maximum agreement rate of 80.3% with expert viewers. It used 20 hidden nodes and was trained for 1508 epochs. Also, neural network gave agreement rates of 75/spl sim/80% with 10 or 30 nodes in hidden layer. We conclude that artificial neural network performed as well as human experts and could be potentially useful tool as clinical decision supporting tool for the localization of epileptogenic zones.
In elastography we are capable of estimating the two in-plane principal strain components following an applied compression, namely the axial and lateral components, along and perpendicular to the compressor/transducer...
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In elastography we are capable of estimating the two in-plane principal strain components following an applied compression, namely the axial and lateral components, along and perpendicular to the compressor/transducer axis, respectively. However, the motion resulting from the compression is three-dimensional. Therefore, in order fully describe the resulting three-dimensional motion we need to also estimate the third strain, or elevational (out-of-plane) component. In this paper, we describe a method that estimates motion, i.e., displacement and strain, in the elevational direction. In a similar way as in the lateral motion estimation, and by assuming that ultrasonic frames are available in more than one parallel elevational planes, we used methods of interpolation and cross-correlation between elevationally displaced RF echo segments. We were thus able to obtain high resolution elevational displacement and strain estimates. An iterative method corrected for motion in the axial and lateral directions. As a result, together with the corrected axial and lateral strain estimates, we obtained the full 3D normal strain tensor resulting from a uniform compression. Results of this method from three-dimensional finite-element simulations are shown.
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