中口 俊哉

In percutaneous puncture simulation, the finite element method is usually used to compute the needle bend and tissue deformation. This method, however, tends to be not suitable for real-time applications such as training systems due to its high computational cost. In this paper, we propose a novel deformable model with a low computational cost. The proposed model reproduces needle bend and tissue deformation in the direction perpendicular to the long axis of the needle. The proposed model consists of a soft tissue deformation model based on the Long Element Method (LEM) and a needle bending model which is designed to be consistent with the tissue model. The parameters for both models are put in the same simultaneous equation to be solved for the simulation. We verified that the proposed model shows a low computational cost by the computer simulation. The accuracy of the model was also evaluated by the experiment using needles and tissue phantoms. The experimental result using only needles showed that a bend could be estimated by the pre-optimized parameters. The optimized parameters were available even if different displacement was given to the manipulated point of the needle.

Many methods have been proposed to restore the blurred images caused by motion blur, camera shake, out of focus and so on. However, little work has been done to restore the blurred images by multiple factors. In this paper, we propose a method for restoration of blurred image by camera shake and characteristics of system response.

デジタルスチルカメラに匹敵する空間解像度を持つカラー動画撮像を民生機器で実現するために，解像度とフレームレートの異なる RGB3 チャネルの動画像を用いて高解像度高フレームレートのカラー動画像を生成する手法を提案する．色分解プリズムと解像度の異なる撮像素子の組み合わせで，色と解像度を同時に分解する．間欠的に取得される G の高解像度画像と R と B の低解像度画像のペアを事例学習して辞書に登録し，毎フレーム取得される R と B の低解像度画像から G の高解像画像を生成する． 1 台のカメラで低解像度と高解像度の事例データが取得でき，かつ，ビデオシーケンスの中から撮影シーンに依存した学習辞書を作成できる．This paper proposes an example-based super-resolution using two kinds of input-image sequences to get a high-resolution, high-frame-rate image sequence. One sequence consists of high-resolution images with low frame rate; the other sequence consists of low-resolution images with high frame rate. The combination of a color-separating prism and three multiple-resolution sensors simultaneously separated the color and spatio-temporal resolutions. The super-resolution of low-resolution red and blue images reconstructs high-resolution green images by referring to the training dictionary. The training dictionary is given as the pair of a high-resolution green image and low-resolution red-and-blue images.

Humeral head (top of arm bone) defect has been diagnosed subjectively by physician. Therefore, it is required to develop a quantitative evaluation method of those defects. In this paper, we propose a quantitative diagnostic method for evaluating humeral head defects by comparing the shapes of the left and right humeral heads. The proposed method is composed of three steps. In the first step, the contour of humerus is extracted from a set of multi-slice CT images by using thresholding technique and active contour model. In the second step, the three-dimensional (3-D) surface model of humerus is reconstructed from extracted contours. In the third step, the reconstructed 3-D shape of left and right humerus is superimposed each other, and then the non-overlapped part is recognized as the defect part. This idea is based on the assumption that human bone structure is symmetrical each other. Finally, the shape of visualized defect part is analyzed by principal component analysis, and we consider that those obtained principal components and contributions represent the feature of the defect part. In this research, seven sets of shoulder multi-slice CT images are analyzed and evaluated.

We propose a new projector-based augmented reality (PBAR) system which can project the image of forceps and a surgical target simultaneously for support of laparoscopic surgery. A compensation method of an error arisen from motion of a body is also proposed to improve the quality of the projection images. It is shown that the system is significant for the forceps insertion by the experiments using the dry-box.

We propose a fast stereo matching algorithm for 3D reconstruction of internal organs using a stereoscopic laparoscope. Stoyanov et al. have proposed a technique for recovering the 3D depth of internal organs from images taken by a stereoscopic laparoscope. In their technique, the dense stereo correspondence is solved by registration of the entire image. However, the computational cost is very high because registration of the entire image requires multidimensional optimization. In this paper, we propose a new algorithm based on a local area registration method that requires only low-dimensional optimization for reduction of computational cost. We evaluated the computational cost of the proposed algorithm using a stereoscopic laparoscope. We also evaluated the accuracy of the proposed algorithm using three types of images of abdominal models taken by a 3D laser scanner. In the matching step, the size of the template used to calculate the correlation coefficient, on which the computational cost is strongly dependent, was reduced by a factor of 16 as compared with the conventional algorithm. On the other hand, the average depth errors were 4.68 mm, 7.18 mm, and 7.44 mm respectively, and accuracy was approximately as same as the conventional algorithm.

We analyzed the influence of ambient lighting to the appearance of still images displayed on the LCD. Four different images under the illumination from the background and over the head were observed and rated by SD method. We found that the appearance is well correlated to the average chromaticity of image and illumination.

Museums hold a wide variety of cultural properties and they organize exhibitions for the public. In history museums, a number of interpretive materials are necessary to present a specific historical theme. However, due to limitation of space, the number of displayed materials is severely restricted. There are various types of guidance systems in museums, however, most systems have not yet responded to visitors' needs. Therefore, a useful guidance system is necessary to satisfy their needs and also to enhance their understandings of the exhibitions. In order to create such guidance system, applications of imaging technology can become a solution to overcome these restrictions and meet the requirements. In this research, a visual guidance system using a data projector was examined in the National Museum of Japanese History. In the kimono (traditional Japanese clothing) section, the projector was used to simulate color changes of the materials under different illuminants. The projector also highlighted areas where annotations were featured in the kimono. The validity of using the projector system was confirmed by results from an interview survey. To further develop this visual guidance system, an augmented reality system consisted of cooperation between the projector and a digital camera was also examined.

In recent years, several methods for evaluation or quantification of video image quality have been studied, such as MPRT (Moving Picture Response Time) for quantification of motion blur occurred on hold-type displays. It is required to improve the methods or criteria to consider human visual characteristics, especially anisotropy and spatio-temporal dependency of contrast sensitivity. In this study, we quantify motion blur of the display by comparing it with static blur edge. We examine the influence of conditions for edge presentation, such as moving speed and moving direction of the edges, on perceived blurriness. According to the results of the assessment, we found that the anisotropy of the display had a significant influence on perception of motion blurs. This result suggests that multidirectional measurement is required to improve criteria of motion blur.

It is important to estimate the noise of digital image quantitatively and efficiently for many applications such as noise removal, compression, feature extraction, pattern recognition, and also image quality assessment. For these applications, it is necessary to estimate the noise accurately from a single image. Cc et al. proposed a method to use a Bayesian MAP for the estimation of noise. In this method, the noise level function (NLF) which is standard deviation of intensity of image was estimated from the input image itself. Many NLFs were generated by using computer simulation to construct a priori information for Bayesian MAP. This a priori information was effective for the accurate noise estimation but not enough for practical applications since the a priori information didn't reflect the variable characteristics of the individual camera depending on the exposure and shutter speed. In this paper, therefore, we propose a new method to construct a priori information for specific camera in order to improve accuracy of noise estimation. To construct a priori information of noise, the NLFs were measured and calculated from the images captured under various conditions. We compared the accuracy of noise estimation between proposed method and Ce's model. The results showed that our model improved the accuracy of noise estimation.

In this paper, spatio-velocity contrast sensitivity functions (SV-CSF) were measured by changing stimuli sizes and viewing distances, and a viewing-condition-dependent model of the SVCSF are build based on these measured data. The viewing-condition-dependent SV-CSF model is particularly required to evaluate and improve moving image quality on large-sized flat panel displays. In the measurements, observers' thresholds of contrast sensitivities were obtained by subjective evaluations by 10 observers. From the experimental results, we found that the peak values of contrast sensitivities to stationary stimuli are varied with relative viewing distances. The relative viewing distance is a normalized distance by the size of display device. The highest peak of contrast sensitivities is observed at the viewing distance of three times size of display device. Based on these measured data, the viewing-condition-dependency of the SV-CSF is modeled as a concave function of the relative viewing distance.

The conventional Koopipat's method was modified to measure the modulation transfer function (MTF) of spatially non-uniform paper First, we analyzed and removed the non-uniform characteristic caused by the fiber structure of paper Secondly, in order to calculate the paper WE the edge spread function (ESF) was analyzed using the edge part of a neutral density (ND) filter superposed on paper A microscope which can illuminate paper from front or back side was used to measure the ESE Gans' method was used to calculate the Fourier transform of ESE MTFs were measured for three types of paper: uncoated paper coated paper and glossy paper, whose graininess levels are high, normal and low, respectively. As a result of the experiment, regardless of graininess level, the MTFs were measured efficiently and accurately. The measured MTF was applied to predict reflectance distribution of monochrome inkjet images from transmittance distribution. We conclude that our method is effective to simulate inkjet printing since the RMSE and difference of average reflectance between the measured and predicted data were low.