This paper presents a method for the automated extraction of emphysematous lesions and quantitative evaluation of their distribution patterns using three-dimensional (3-D) CT images. Multi-detector row CT scanners enabled us to obtain volumetric CT images at high resolution. Most of studies of computer-aided diagnosis for pulmonary emphysema process and analyze low attenuation areas in CT images using two-dimensional image processing techniques. Few studies have used three-dimensional image processing techniques. It is possible to obtain the spatial distribution of emphysematous lesions by 3-D image processing techniques. We studied here the application of computer-aided diagnosis for pulmonary emphysema using 3-D image processing techniques. We extracted emphysematous lesions automatically using a region growing method. In order to analyze the distribution of the low attenuation areas detected, we examined the relation between emphysematous lesions and bronchi or blood vessels using Euclidean distance transformation or lung dividing. We applied the proposed method to real 3-D X-ray CT images. Experimental results showed that the method could extract emphysematous lesions and quantitatively evaluate the distribution patterns of the lesions.

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Respiratory sinus arrhythmia (RSA) is known as a selective index of cardiac vagal activity. RSA is usually extracted at a power of 0.15Hz-0.5Hz using spectral analysis. We propose a new method to extract RSA as a waveform under free breathing. First, we interpolate the RR interval (RRI) of the electrocardiogram signal by the derivative of cubic spline interpolation (DCSI), and calculate respiratory phase using Hilbert transform. Then, we extract the instantaneous RRI at every π/10 rad of the respiratory phase as the RSA waveform. Since DCSI has no delay in interpolation, instantaneous RRI keeps in phase with the variability of respiration. We extract the RSA waveform with each breath and can easily evaluate the accuracy of extraction and investigate the effect of volume or interval of respiration. Furthermore, a breath that is too short or too long in terms of the RSA frequency is removed, so it is possible to improve the accuracy of extraction. We experimented using seven subjects who conducted free breathing in resting and sitting positions for 30 minutes. Electrocardiograms and inductance plethysmographs were used at the rate of 1kHz and 100Hz, respectively, and we extracted the RSA waveform. From the analysis of mean RSA waveform, maximum point and minimum point appeared approximately at π rad and 2π rad, respectively. This result confirms that the amplitude of RSA in one breath is extracted by subtracting the RSA waveform in π rad from that in 2, π rad. From the analysis of RSA in one breath, we evaluated the accuracy of extracted RSA by S. D. in periods of 5 minutes, and obtained a value of 3.7ms. We also found that there was a positive correlation between the amplitude of RSA and the volume of respiration and interval of respiration under free breathing.

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The awake background electroencephalogram (EEG) is the basic EEG for EEG interpretation, and it is important to represent its characteristics quantitatively. We have already proposed an EEG model consisting of sinusoidal waves with Markov process amplitude. This model can represent the characteristics of background EEGs appropriately, especially the αrhythm, which is the most important. However, slow waves(δandθwaves)have slightly different characteristics-both the amplitude and frequency fluctuate. Inthisstudy, an EEG model consisting of sinusoidal waves with fluctuating amplitude and frequency was proposed to represent the characteristics of slow waves accurately. The theoretical power spectrum of the model was derived and used for determining the model parameters in the frequency domain. The αandβ
waves were represented by sinusoidal waves with amplitude fluctuationonly, while the δandθwaves were represented by sinusoidal waves with fluctuation of both amplitude and frequency. The features of the time series of the constructed model were compared with those of the raw EEG and satisfactory results were obtained. Furthermore, the rhythmicity of slow waves was quantitatively represented using the proposed model.

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It is reported that magnetic stimulation has good efficacy in treating urinary incontinence. A current pulse is passed through a coil near the body, and the resulting time dependent magnetic field induces an electric field in the body. Magnetic stimulation offers two main advantages over electrical stimulation: it can be applied without removal of clothes, and it involves little pain. However, the distribution of current in the living body is not clearly known. Authors therefore attempted to make a computer simulation model of the female abdomen and simulate the distribution of induced current on the basis of tissue conductivity. This paper reports making a computer simulation model and analyzing the distribution of induced current by time varying magnetic fields. The authors also compare current distributions in the living body induced by different coil configurations and discuss which method of stimulation is the most efficient.

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The equivalent cross-relaxation rate (ECR) is a measurement method that can evaluate a change in organization structure quantitatively utilizing MRI. The goal of this study is to discover a parameter that we can use to evaluate aging of the human brain using ECR. Fourteen patients diagnosed with diseases other than those located in the cranium were imaged using a SIGNA model of GE Medical Systems equipped with a 1.5 T clinical scanner. The ECR values were defined as the percentage of signal loss between unsaturated and saturated images. It was found that the ECR value of gray matter was lower than subcortical white matter. At ages under 70 years old, the mean of ECR values of subcortical white matter showed stable values with insignificant variance. Furthermore, there was no correlation between age and ECR value of every region calculated. On the other hand, it was found that there was a negative correlation for the ECR values of subcortical white matter and gray matter at ages slightly over 70 years old. It is possible that the reduction in ECR value shows demyelination by aging in the senium. When the offset frequency is near the water resonance frequency, the ECR values mean information about neurocytes. Accordingly, the ECR (320)/ECR (1200) value probably shows that information is related to the amount or activity of neurons.

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