This paper describes a ROI (Region Of Interest) usit segmentation and a smoothed border detection in an ultrasonic echo cardiotomogram. The segmentation by texture analysis roughly partitions the image into three parts (blood, cardiac muscle and epicardium). Then, the gravity center of boundary ROI and spline functions yield smoothed borders in detail. A result of an example shows usefullness of this method.

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This paper describes two new functions—automatic femoral movement and interbony distance measure that have been required by surgeons to improve the efficiency of surgical planning for hipjoint with computer. By these functions we provide surgeons an automatic simulation procedure to fit femur into pelvis that will increase the contact area, and also a new method to measure the distance between femur and pelvis from X-ray CT images. We also discuss the error in this measurement method and show some photos of a pre-operative surgical planning with the new functions. According to the surgeon who has used the new functions, they work efficiently for pre-operative diagnosis and surgical planning.

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This paper presents a 3-D segmentation method that automatically extracts soft tissue from multi-sliced MRI head images. MRI produces a sequence of two-dimensional (2-D) images which contains three-dimensional (3-D) information of organs. To utilize such information we need effective algorithms to treat 3-D digital images and to extract organs and tissues of interest. We developed method to extract the brain from MRI images which uses a region growing procedure and integrates information of uniformity of gray levels and information of the presence of edge segments in the local area around the pixel of interest. First we generate a kernel region which is a part of brain tissue by simple thresholding. Then we grow the region by means of a region growing algorithm under the control of 3-D edge existence to obtain the region of the brain. Our method is rather simple because it uses basic 3-D image processing techniques like spatial difference. It is robust for variation of gray levels inside a tissue since it also refers to the edge information in the process of region growing. Therefore, the method is flexible enough to be applicable to the segmentation of other images including soft tissues which have complicated shapes and fluctuation in gray levels.

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A bioelectrode was constructed with the electrolyte from ion-conducting adhesives (ICA) which complexed a segmented polyether-urethane with LiClO₄. Electric characteristics and sticking properties of the electrode were examined. The following results were obtained. Impedance on a pair of electrodes was 0.53-1.45kΩ. Contact impedance to human skin was 18.5kΩ at 1kHz, 55.6kΩ at 10kHz and 156kΩ at 50kHz. Voltage on a pair of electrodes was ±1.0-±2.0mV. Stability for voltage on a pair of electrodes was 2-6μV. Change for voltage on a pair of electrodes by direct current was 48-50mV. These values were within the limits of the standard for disposable electrocardiogram (ECG) electrodes. The ICA showed tolerance for electrical load. Good adhesion and high safety to human skin were also ascertained. Based on these results, clinical applications of the ICA electrodes were attempted for ECG measurements and low-flequency current therapy. The results confirmed applicability of ICA to bioelectrodes for ECG and low flequency electrical stimulation devices.

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We calculated the effect of 1) airway reactance, 2) extrathoracic airway shunt impedance, 3) heating and humidification of inspired air, 4) abdominal gas volume and 5) respiratory quotient on the measurement of phase difference between chest flow (V_c) and mouth flow (V_m) using computer simulation. 1) When airway impedance (Z_a) was approximated to be a simple airway resistance as we did in the former paper to evaluate the effect of airway impedance on V_c-V_m phase difference, the phase difference (θ_r) was calculated to be 0.8% less than that (θ_s) calculated from Z_a including airway inertance and shunt compliance in normal lung. θ_s became larger than θ_r when the peripheral resistance increased, but it was suspected that the difference ratio of θ_s and θ_r does not exceed 5%. 2) The influence of extra-thoracic shunt impedance was within 0.1% regardless of the variation of the respiratory frequency, airway impedance and VTG. 3) The difference ratio of the heating and humidification of the inspired air was calculated to be within -3% when the time constant of delay (d) was assumed to be 0.02 second. The difference ratio became higher as d increased, but it may not exceed -5% as far as d was within 0.1s. The influence of the abdominal gas was calculated to be much variable in correspondence with the abdominal gas volume or the respiratory pattern, but it was inferred to be within 5%. 5) The influence of the respiratory quotient was calculated to be negligible. As a result, it may be concluded that all the factors discussed above do not become an obstacle to the clinical application of this method to the evaluation of the pathological change in obstructive airway disorders.

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A new method for automatic integrative interpretation of the awake electroencephalogram (EEG) was developed. We first determined all the items necessary for EEG interpretation following the procedure that a qualified electroencepharographer (EEGer) goes through for the visual inspection of awake EEG, and then defined each item quantitatively. For the automatic interpretation, we determined specific EEG parameters for each item so that they can fit the graded judgment of the item by the qualified EEGer as closely as possible. Those specific EEG parameters were actually calculated from periodograms of the EEG time series. The automatic EEG interpretation system thus established was applied to the EEG data of 14 subjects, and the results were compared with those obtained through the visual interpretation by the EEGer. This automatic EEG interpretation was found to be in good agreement with the visual interpretation by the EEGer in most EEG records, The proposed method for automatic integrative interpretation of EEG can be used clinically as an assistant tool for neurologists and EEGers, and may be the first step for its clinical application to the hospital use.

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A new method for the prediction of the post-operative face shape in craniofacial surgeries was developed by using image processing and computer graphics. The post-operative face shape can be viewed in arbitrary three-dimensional (3D) directions, since it is predicted in a 3D world based on a convensional 2D schemes on a regular X-ray film. We have applied the proposed method to an actual patient after simulating a craniofacial surgery to the lower jawbone. The result showed that the predicted configuration of skin surface was well simulated.

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