中口 俊哉

This research proposes the deformation model of organs for the development of the medical training system using Virtual Reality (VR) technology. First, the proposed model calculates the strains of coordinate axis. Secondly, the deformation is obtained by mapping the coordinate of the object to the strained coordinate. We assume the beams in the coordinate space to calculate the strain of the coordinate axis. The forces acting on the object are converted to the forces applied to the beams. The bend and the twist of the beams are calculated based on the theory of structural mechanics. The bend is derived by the finite element method. We propose two deformation methods which differ in the position of the beams in the coordinate space. One method locates the beams along the three orthogonal axes(x, y, z). Another method locates the beam in the area where the deformation is large. In addition, the strain of the coordinate axis is attenuated in proportion to the distance from the point of action to consider the attenuation of the stress which is a viscoelastic feature of the organs. The proposed model needs less computational cost compared to the conventional deformation method since our model does not need to divide the object into the elasticity element. The proposed model was implemented in the laparoscopic surgery training system, and a real-time deformation can be realized.

In this Paper, an image quality of movies displayed on the LCD and the PDP is compared and analyzed on the basis of subjective and objective evaluation experiments. Nineteen kinds of movies with different dynamic range, saturation, contrast, colorfulness and motion blur are prepared and evaluated by observers. Various kinds of physical values such as luminance and chromaticity of each movie and MPRT displayed on the LCD and PDP were also measured and analyzed. The relationship between observer rating values and those obtained physical values is compared and discussed.

It is considered that the gazing area obtained by the eye tracking camera is the most important region of the image. From the analysis of the gazing area for various kinds of the images, gazing area is well correlated to the truncated region of color, density, and movement. In this paper, we propose a new method to extract saliency region automatically corresponding to the gazing area from the video image.

For a long time, endoscopic diagnosis are performed for various diseases without changing color settings. However, since for example the color feature of early stage cancers is too small to detect, it is very significant to enhance endoscopic images by using the customized parameters of the color collection. In this research, we propose a new color collection method considering the index value of Hemoglobin density, and develop a new user-interface for the medical doctors, which makes the decision of the optimum values of multiple parameters quite easy. By deciding the adequate parameters for various cases of early stage cancers, the effectiveness of the color collection method can be confirmed.

In a previous paper, we have proposed an image quality metric by using the gazing information obtained from the measurement of eye movement. In this method, we only consider the spatial change of the gazing information. However, the change of the concentration with time was observed during the subjective evaluation experiment. It is considered that the temporal change of the gazing area is relevant to the importance of the observed gazing area. Therefore, it is necessary to consider the temporal change of the gazing area. In this paper, we measured the eye movement of the observers when they performed the evaluating of the quality of the displayed image on the PDP(Plasma Display Panel) for 15 seconds every 3 second. We analyzed the gazing area of each 3 second. The results show that the gazing area from the first to the third 3 second increases, and it will decreases from the fourth or the fifth 3 second.

In conventional laparoscopic surgery, one medical doctor who only holds the laparoscope during the surgery is required. Therefore, in this study, we introduce an automatic tracking and zooming system for laparoscopic surgery by means of a steady laparoscope on the abdominal surface. The system can be added to a conventional laparoscopic system and can analyze camera images in real-time. The markers of this system are attached at the top of the forceps and extracted, and the focusing area can be estimated. In this study, we introduce two marker tracking algorithms; one tracks a single marker on the forceps, which is assumed as the focal point; and the other tracks two different colored markers, which can estimate a more practical focusing point. In order to perform high-quality real-time movie processing, the system uses a CPU and GPU (graphics processing unit) in parallel. The tracking algorithm is carried out by the CPU, image enlargement is carried out by the GPU, and then a high frame rate and low delay time are achieved. For the automatic smooth camera work, a new control model with many parameters is proposed. Through animal experimentation was performed six times, and appropriate values of parameters evaluated by two experienced doctors were obtained. After the evaluations of the experienced doctors, the effectiveness of the system was proven: cholecystectomy successfully conducted in animal experiments without the support of a scope-holding doctor.