畑 豊

人工膝関節置換手術後,生体内の人工膝関節の動作機能評価にはX線透視画像が広く用いられている.従来様々な,X線透視画像を用いた動作機能評価法が提案されてきたが,Occlusionが発生している画像への適用は困難であった.そこで本研究では,Occlusionが発生している画像に適用可能な人工膝関節の動作機能評価法を提案する.提案手法は,X線透視画像と人工膝関節の3次元形状データを用い,ファジィイメージマッチングにより,人工膝関節の位置・姿勢を認識し,動作機能を定量化する.本提案手法をシミュレーション画像,ファントム画像,被験者の画像に適用した結果,Occlusionが発生した画像においても,動作機能評価に有効であることを確認した.

Unconstrained health monitoring systems have received much considerable attention in medical applications, because such system can examine a subject without constraint. In this study, we propose a detection method based on a fuzzy logic for evaluating heart rate using our ultrasonic vibrograph. In the experiment for confirming heart rate, our method has been successfully used to detect the heart rates of four subjects, compared with a method using an electrocardiograph.

痴呆性疾患は大脳全体が同じ割合で萎縮するのではなく,痴呆ごとに萎縮する脳葉に違いがあることがわかっている.そのため,大脳を区分し,前頭葉,頭頂葉,側頭葉,後頭葉単位の体積を測定することは痴呆症の鑑別,経過観察に非常に有用である.本稿では,各葉間の境界をfuzzy rule-based ASMを用いて最適な形状に変形し,3次元頭部MR画像から各葉を自動的に区分する方法を提案する.再現性の評価のため,提案法を3人の被験者に適用しユーザ毎の体積のばらつきを調べた.1人のエキスパートと3人の初心者は各被験者につき1つの3次元画像を10回ずつ区分した.その結果,提案システムを用いることによって高い再現性で大脳を区分できた.

これまでFuzzy C-means (FCM)、Bayesian Classificationなどの様々なクラスタリング法が医用画像の領域分割に用いられてきた。しかし、ほとんどのクラスタリング法は数値データのみを対象とし、名義データを扱えないもしくは扱うのに数値化が必要であるため、領域分割への応用においても、数値で表現できる画素値などの情報しか使えなかった。そこで、本研究では名義データを効率的に扱えるラフ集合論による画像の領域分割法を提案する。本提案法では、しきい値処理とラベリングにより求めたラベル番号をクラスタリングの属性値とする。すなわち本提案法では、従来の画素値に基づくクラスタリングではなく、画素の連結関係に基づくクラスタリングを可能とする。また本文では本手法の性能を評価するため、提案手法を頭部MRI画像に適用し、その真値画像と比較し数値的な評価を行う。

Investigating the shape and time to peak (HR delay) of hemodynamic response (HR) introduces a new facet of researches on human brain function. We have proposed an analysis method for detecting activated areas and measuring HR delay simultaneously using event related function magnetic resonance images (ER-fMRI). The method has been based on wavelet transform. In this paper, we investigate the performance of the method by modifying a mother wavelet. The modified mother wavelet is based on mathematically defined HR function by SPM (statistic parametric mapping) software by Friston et al. To evaluate the proposed method, we applied the proposed method and conventional methods to the phantom data. The results showed that the method could detect the activated area equivalent to and more than conventional methods. We also estimated the accuracy of measuring HR delay. The results showed that the proposed method could measure HR delay more accurate than the conventional method.

The human lung is composed of five compartments called "Lung lobes." Segmenting lung lobes from chest Multidetector-row Computed Tomography (MDCT) images can provide effective information for analyzing pulmonary conformation and detecting pulmonary diseases such as the emphysema. Our method finds the boundary surface between lung lobes by the fuzzy control that fits a curved surface into the space with lower density of tubular tissues, which are defined as peripheral blood vessels and bronchus. This paper describes the performance evaluation of the proposed method and the application method for estimating the forced vital capacity of individual lung lobes.

Investigating the shape and time to peak (hemodynamic response [HR] delay) of the HR introduces a new facet of research on human brain function. This paper proposes a novel method for analyzing event-related functional magnetic resonance images (ER-fMRI). The method is based on wavelet transform. The principal feature of the method is that it can detect an activation area and estimate the HRF simultaneously. To evaluate the proposed method, experiments were done on phantom data and human subjects. The results showed that the method could detect the activation area equivalent to and more than SPM99. Then, examination of variability of HR delay among the activation areas suggests that HR delay at the motor area is significantly faster than that at the visual area. © 2004, Elsevier Inc. All rights reserved.

We propose a method for estimating the pose/position of a guiding reference object using both camera images and 3-dimensional model data of the guiding object. Our objective is to identify the object position/pose and to move an optical pointing device (laser pointer) mounted on an active camera so that LED light is pointed at the desired orientation and position. During a surgical procedure, probe positioning should be achieved at precisely desired position and orientation. For this purpose, we update input images of a camera on the pointer and iterate estimations by moving the camera. This iterative approach with updated images makes the pose/position parameters to be estimated more accurately than approaches with only one image. Though iterated estimation generally increases the computational effort, estimation task is achieved with improvement in speed by the approach with changing image resolution. Through some experimental results, we show that the proposed method is effective for guiding system.

Investigating the shape and time to peak, called HR delay, of hemodynamic response (HR) gives a novel tool to analyze a human brain function. We have proposed an analysis method for detecting activated areas and measuring HR delay simultaneously. In this paper, we improve the performance of the method by modifying a mother wavelet. The modified mother wavelet is based on mathematically defined HR function by SPM (statistic parametric mapping) software by Friston et al. To evaluate the proposed method, the proposed method and conventional methods are applied to phantom data and human subjects. The results indicated that the proposed method could detect activated areas with equivalent to and more accurately than the conventional methods.

In this paper, we propose the novel method for 3D shape reconstruction of object using an extended Kalman filter with a single active camera. In conventional methods, the laser scanner or stereo camera is often used as the sensor to reconstruct 3D shape. However, they have large-scale system and some problems caused by it. We use only one active camera for shape reconstructing. Since an active camera takes time-series images, some points can be observed and 3D position of the points estimated by extended Kalman filtering. Also, we consider the reconstruction of 3D geometry from the connection between each point, and plan good camera's viewpoints. After estimating 3D position of two selected points on the object and analyzing them, the active camera moves to the next viewpoint for obtaining the hidden information. By using these estimates of points from some planned viewpoints, 3D shape reconstruction is achieved. We apply the proposed approach to the images of computer simulation and real world, and we show that it is effective for shape reconstructing of object.

We propose a novel method for detection of a moving object in an image sequence. This purpose is achieved by using discrete wavelet transform and extended complex Kalman filter(ECKF) in the transform/spatio-temporal mixed-domain. The moving objects arc considered as arbitrary trajectory signals(ATS). A trajectory signal in mixed-domain is a bunch of l-dimcntional complex signals. And an ATS is a bunch of quasi-periodic signals with pitch fluctuations in mixed-domain. A parallel bank of ECKFs is employed for the estimation of quasi-periodic signals. In addition, these estimates can be combined with depending on the energy of the subband images. Experimental results show the moving object is detected effectively.

This paper describes an ultrasonography system of implant in bones aided by fuzzy logic, Although conventional X-ray CT method can visualize the implant in the CT table, it has serious disadvantage of X-ray exposure. Therefore, we require the system which can be used the orthopedic surgery with no X-ray exposure, This paper solves the problem in an intramedullary nail by our ultrasonic device and fuzzy logic techniques. We localize the distal transverse screw hole in the nail under surgeries for femur fracture. Their screw hole positions are identified by calculating two fuzzy degrees of intensity and the variance. As the result, our experimental result shows that our system can identify their screw hole positions within error of 2.5 mm.

This paper introduces rough sels theory into image segmentation problems. The proposed image segmentation method considers that an image is an information system and a pixel in the image is a datum of the information system. The feature values of the pixels reflect connectedness between pixels. With respect to connectedness, the proposed method extracts alpha-tolerance relation, which is an extended concept of rough sets, from the information system. The categories of the alpha-tolerance relation mean regions in the image. Consequently, for each region pixels have high connectedness to other pixels of the region. To evaluate the performance of the proposed method, it wax applied to MR images produced by the BrainWeb computer simulation. The experimental results showed that the proposed method segmented the given MR image with high lnimngeneity.

This paper describes a diagnosis system for bonding degree of femur stem by using ultrasonic wave. In general, doctors perform the surgery with considering the bonding degree by their subjective judgment, which depends on inter- and intra- doctor. Therefore, development of the diagnosis system that provides a criterion of the bonding degree contributes them to perform the surgery. Proposal system estimates the bonding degree from the acoustic energy obtained by transmitting the ultrasonic wave from the end of the stem. We employ fuzzy logic to deal with the relationship of acoustic energy, bonding degree, and load. The proposal method was applied to eight cases that the stem was given different loads each other. The correlation coefficient between the real load and the estimated load was 0.9353.

In this paper, we propose the novel method for estimating the three dimensional position and pose of the object by using only one active camera. Our method estimates the depth length from the camera to the object by a Kalman filter. Kalman filter enables the depth distance estimation with high accuracy by using one camera and decreases the number of the iteration by estimating the accurate depth distance. Moreover, we iterate the estimation by updated input images. Although the distance from a camera to the object was about 600mm, the experimental results showed that the estimated error of the depth length was about 2.4mm.

In this paper, we propose a method to generate arbitrary viewpoint images of unknown objects using a single camera set in a known environment. In recent years, various methods for generating arbitrary viewpoint images have been proposed. These methods often use multiple cameras. When we can generate the arbitrary viewpoint images using only a single camera, we can apply the technique to more various fields. Therefore, we propose the arbitrary viewpoint image generation method by using a single camera and the information of the known environment (size of a room, and the relation between the room and the camera). We set the camera at the rectangular parallelepipeds room and unknown objects on the floor. We generate the arbitrary viewpoint images using the estimated three-dimensional (3D) information of the unknown objects and the known environment information. In the experimental results, we show that the proposed method can estimate the 3D information of the unknown objects and generate the arbitrary viewpoint images.

In conventional transcranial sonography system for human, available window of skull in adults is limited to the temporal bone. Visualization of an int4racranial tissue from all angles can support to diagnose the brain disease with high accuracy. However, no transcranial sonography system has been developed. This paper describes transeranial ultrasonography system based on anatomical knowledge. Generally, it is difficult to visualize intracranial tissues from frontal bone because of large attenuation in skull. To overcome this difficulty, we employ fuzzy signal processing and human brain anatomical model. In our system, we can successfully extract the skull and the brain surface for human. As u result, our method could visualize two-dimensional skull and brain surface.

Forced vital capacity (FFC) of individual lung lobes is important information for thoracic surgeries such as the living-donor lobar lung transplantation. However, conventional methods for measuring the FVC of individual lung lobes have not considered the variation of the labor function among subjects. This paper proposes a new method for measuring the FVC of individual lung lobes using Multidetector-row CT. The method first estimates contribution ratios of individual lung lobes for the FVC of whole lung. Using the estimated contribution ratios and the FVC of whole lung measured by a spirometry, our method estimates the FVC of individual lung lobes. As a result of applying the proposed method to five normal subjects, we could successfully measure the FVC of individual lung lobes.

This paper proposes a real-time position and pose tracking method of a moving object. The conventional methods need a three-dimensional (3D) model data of the target object. By the proposed method, the 3D position and pose tracking can be achieved without the 3D model data. We set some landmarks to estimate the 3D position and pose of the object by a single camera. In addition, the trajectory of moving landmarks is estimated by a Kalman filter. The experimental results show that a stick with a diameter of 5.0 mm can be inserted in a moving pipe with a diameter of 30.0 mm in real-time.

This paper describes an automated medical diagnosis system (AMDS), which determines a normal degree for a medical sign or disease based on fuzzy logic. First, we summarize normal degree on theory of hierarchical definability (THD) by Zadeh. Second, we show flow chart of AMDS, which consists of two parts; one is construction of AMDS and the other is calculation of normal degrees. Third, we demonstrate two examples of AMDS: one is AMDS for diagnosing Alzheimer disease and Frontotemporal dementia and the other is personal AMDS for diabetes. Finally we conclude technical results.

MR cholangiography (MRC) is a commonly used imaging method for diagnosing the pancreatic duct. This article proposes a novel method for enhancing medical images called target image enhancement using representative line (TIER), and its application to MRC images. Our method first finds the representative line (RL) of the pancreatic duct using a fuzzy if-then rule. TIER presumes the approximate region of the pancreatic duct using the obtained RL, and then emphasizes the intensity in the approximate region. Therefore, our method does not require any segmentation procedures, which often may be hard work. We evaluated the ability to find the RL and to estimate the approximate region of the pancreatic duct by applying the proposed method to computer-simulated data and MRI phantom data. We also show the image-enhanced images for normal and abnormal patients. © 2004 Wiley Periodicals, Inc.

北海道余市町沿岸のホッキガイ漁場において、底質性状、底質攪乱の程度およびマクロベントスの群集構造を解析することにより、本種の生息環境を評価した。底質性状は水深の増加に伴って粒径が細かく、有機物含量が増加する傾向を示した。粒径の変動に明瞭な季節性は認められなかったが、有機物含量は春-夏に上昇し、秋-冬に低下した。底質攪乱は水深の増加に伴って緩やかになったが、各地点の攪乱の程度は波浪の季節変化や海岸地形の影響を受けて大きく変動した。水深9m以浅は年間を通してハイイロハスノハカシパン、ホッキガイ、ツノヒゲソコエビ科の端脚類、キサゴおよびキョウスチロリが優占する群集に覆われていたが、水深12m以深は構成種の新規加入によって群集の分布パターンが変化した。ホッキガイの分布域は、本種の生息に適した底質性状を示したが、底質攪乱による減耗やハイイロハスノハカシパンとの空間競合の可能性が指摘された。

This paper proposes an automated 3D visualization method of embedded tubes applicable to the scanned result of pulse-radar Non-Destructive Testing (NDT). The proposed method consists of three stages. First, our method defines the processing region which includes a pattern generated by a tube. This region is determined by referring to the composition of a received wave. Second, after expert knowledge of a tube is translated into fuzzy inference rules, the positions of embedded tubes are identified by inferring them. Third, 3D links of the identified positions are formed to visualize the continuous shape of the tubes. Consequently, the tubes are extracted, and their 3D shapes are visualized. The experimental result on the specimens shows that our method was able to find all tubes that exist in the radiograph and the schematic. Our method could thus provide the internal information of concrete with sufficient accuracy required in the practical construction work.

This paper proposes an automated 3D visualization method of embedded tubes applicable to the scanned result of pulse-radar Non-Destructive Testing (NDT). The proposed method consists of three stages. First, our method defines the processing region which includes a pattern generated by a tube. This region is determined by referring to the composition of a received wave. Second, after expert knowledge of a tube is translated into fuzzy inference rules, the positions of embedded tubes are identified by inferring them. Third, 3D links of the identified positions are formed to visualize the continuous shape of the tubes. Consequently, the tubes are extracted, and their 3D shapes are visualized. The experimental result on the specimens shows that our method was able to find all tubes that exist in the radiograph and the schematic. Our method could thus provide the internal information of concrete with sufficient accuracy required in the practical construction work.

This paper describes a computer sided support system for localizing the distal transverse screw hole in interlocking intramedullary nailing. It is required to localize the distal transverse screw hole under surgeries for femur fracture. Conventional X-ray CT method can find the hole in the CT table. In it, when we move patients from the CT table to the surgery table, the exact potion is missed. Therefore, a real time determination of the hole position is required to enhance the quality. This paper solves the problem by using an ultrasonic system aided by fuzzy logic. First, we show the details of the equipments. Second fuzzy inferences effectively determine the fuzzy degree being the screw hole inserting to cattle femur. Finally, the experimental result shows that our system can determine the screw hole with 1.0mm of error.

Functional assessments of the meniscus assists to diagnose diseases of the knee joint. To estimate the degree of the degeneration of the injured meniscus, this paper proposes an automated method for segmenting the region of the meniscus from multidetector computed tomography (MDCT) images. The novel feature of the proposed method is that we segment the meniscus based on a fuzzy rule-based representative line finding algorithm. The representative line, which is a new concept, is a line that abstracts the position and shape of the meniscus. Experimental results on the extended and flexed knee joints for three healthy subjects show that our method found a proper representative line, and segmented the meniscus successfully.

© 2003 IEEE. We propose the method for position/pose identification and manipulator navigation to the desired position using one camera and three-dimensional CAD model. In position/pose estimation, instead of simultaneous estimation of all position/pose parameters of target object, the parameters are severally estimated with image features. Thus, our method consists of position parameters estimation; pose parameters estimation and manipulator navigation to the desired position. The position parameters are estimated approximately with image features, and then pose parameters are estimated. And then, a manipulator to the desired position based on the estimates is moved. Both estimation and movement are repeated until the manipulator reaches to the desired position. This gradual approach achieves manipulator navigation concerning automation works with improvement in speed and accuracy.

© 2003 IEEE. Segmentalion of lung lobes from MDCT images can provide effective information for functional assessments of each lobe and detection of pulmonary diseases such as the emphysema and Jung cancers. Conventional studies have detected pulmonary fissures that located between lung lobes. However, some parts of fissures may disappear in MDCT images because of artifacts or the adhesion between lung lobes. This paper proposes a novel method for segmenting lung lobes based on tubular tissues, which are the peripheral blood vessels and bronchus. Our method estimates the boundary surface between lung lobes by fitting a curved surface. The fitting is performed with fuzzy control, and it searches the boundary where the density of tubular tissues is low. As a result of applying the proposed method to two normal subjects, we could estimate the boundary surface between lung lobes and segment lung lobes successfully.

© 2003 IEEE. This study introduces a novel method for enhancing MR cholangiography (MR-Q images based on representative line finding algorithm. The method enhances the images using the representative line (RL) of the pancreatic duct. The RL is tracked by finding the most suitable direction that is decided by means of fuzzy inference techniques. The tracking performance was evaluated by computer simulation, and by applying our method to MR-C images of tube-formed phantoms. The results showed that the proposed method could correctly find the RL of the objects. The diameters of the tube-formed phantoms were estimated with high accuracy. Then, the proposed method was applied to enhance MR-C images of four normal volunteers and one patient. In alt cases, the pancreatic duct was enhanced clearly.

© 2003 IEEE. This paper defines normality in human body for diagnostic analysis of signs observed in human body. The normality is a matter of degree. Physician usually examines whether a patient is either normal or abnormal. Diagnosis of human body is usually done by observing biosignals, radiological images, body surface information and others of human body. First, the information granularity of these signs of human body is shown. The normality is defined in the theory of hierarchical definability. According to the definition, a calculation method of the degree of normality is introduced. Finally, the examples of the degree of normality are shown.

This paper proposes an automated method for finding the Willis ring from the human brain MR angiography (MRA) images, which can depict cerebral arteries with high contrast. It strongly helps screening of unruptured cerebral aneurysm in MRA images. The proposed method consists of (1) segmenting cerebral arteries from MRA images, (2) skeletonization of artery trees, and detection of furcations, and (3) finding furcations in the Willis ring using genetic algorithm (GA) based on fuzzy knowledge base (fuzzy KB). Fuzzy KB gives knowledge about the Willis ring that consists of arteries and furcations. GA finds a set of furcations by optimizing an objective function. The objective function used by GA estimates fitness of a set of furcations using fuzzy KB. Our method was first applied to a 3-D phantom data generated by computer simulation. The result demonstrated that our method detected all suitable furcations correctly. Next, it was applied to MRA volume data of two normal healthy volunteers. In any cases, the proposed method detected desired all furcations in the Willis ring.

Periodic inspection for degradation of insulating oil in transformers requires for preventing outage. However, conventional methods were not suitable for that, due to a large size of the measurement system and requirement of sampling. This study aims to develop the ultrasonic evaluation system satisfying these requirements aided by fuzzy inference. The system evaluates degradation, and it estimates kinetic viscosity. In the experiment, we applied our method into six kinds of insulating oils. As a result, correlation coefficient between our estimation and viscometer were over 0.92. Thus, our method correctly determines degradation of insulating oil.

Periodic inspection for degradation of insulating oil in transformers requires for preventing outage. However, conventional methods were not suitable for that, due to a large size of the measurement system and requirement of sampling. This study aims to develop the ultrasonic evaluation system satisfying these requirements aided by fuzzy inference. The system evaluates degradation, and it estimates kinetic viscosity. In the experiment, we applied our method into six kinds of insulating oils. As a result, correlation coefficient between our estimation and viscometer were over 0.92. Thus, our method correctly determines degradation of insulating oil.

We describe a new automated method for detecting embedded objects in the ultrasonic non-destructive testing (NDT) system. A-scan waves collected by our developed system are converted into a B-scan image. The sensor system has the noise signals independent from targets to be detected. In the ultrasonic NDT system, the signals are due to disturbing of echoes produced by the transducers and multiple reflections. These signals are called inherent wave. This paper first proposes the estimation method of the inherent wave from the B-scan image. After this method subtracts the inherent wave, the resultant image (suppression image) is considered as the image consisting of only echoes from the embedded objects. Second, analysis of the intensity histogram of the suppression image leads the candidate points of embedded objects. Finally, fuzzy if-then rules can' represent information on distribution of the intensity histogram and the homogeneous intensity levels of the objects. Evaluated degrees from the inference results can demonstrate the embedded objects. The method was applied to concrete members with reinforcing bars, resin tubes and steel pipes. The experimental results showed that this method was able to automatically detect the embedded objects with high accuracy and to display the location of embedded objects.

This paper presents a rough sets-based method for clustering nominal and numerical data. This clustering result is independent of a sequence of handling object because this method lies its basis on a concept of classification of objects. This method defines knowledge as sets that contain similar or dissimilar objects to every object. A number of knowledge are defined for a data set. Combining similar knowledge yields a new set of knowledge as a clustering result. Cluster validity selects the best result from various sets of combined knowledge. In experiments, this method was applied to nominal databases and numerical databases. The results showed that this method could produce good clustering results for both types of data. Moreover, ambiguity of a boundary of clusters is defined using roughness of the clustering result.

言語優位半球の判定は, これまで後遺症の危険を伴ったWadaテストが用いられてきた.近年, 近赤外分光法(NIRS)の原理を応用した光トボグラフィ装置が, 言語野の解析に適用できる無侵襲な方法として用いられるようになってきた.本文ではファジィモデルを用いた言語優位半球判定法を提案する.本方法は, まず言語野の所属度をファジィモデルを用いて表現し, 言語野の同定作業を行う.次に言語野の所属度に基づいた左右性指標の計算を行う.本文では3例に適用し, 本方法は言語野の同定に有効であることを示した.

functional MRI (fMRI)とは頭部MR画像の連続撮像を行い, MR信号の時間変化から脳機能を解析する技術である.刺激に伴い賦活の生じた領域ではMR信号が上昇し, やがて信号はベースラインに戻る.これをヘモダイナミクスレスポンス(以下HR)という.本文ではウエーブレット変換を用いた賦活領域の同定, HR反応遅延を計測するfMRI解析法を提案する.実験では20例のfMRIデータに本方法を適用した.本方法の賦活領域の同定精度はSPMと同等であり, さらにHRの遅延の計測が可能である.また, 本方法を用いることで補足運動野と運野においてHRの遅延に有意差があることが初めて確認された.

脊椎疾患の手術療法において, 術者が脊椎神経を損傷する危険性があるため, 現在はMRやCTによる脊髄造影画像で術前に脊椎内の神経の状態を観察する.しかしこれらの画像は2次元画像で, 医師が関心領域である硬膜嚢の正確な3次元形状を認識するのは困難である.組織間の形状を術前に把握できる支援システムの開発が望まれている.そこで本研究では, 支援システムの基礎となる腰部MR画像からの硬膜嚢の自動抽出法を提案する.本抽出法は硬膜嚢の形状に関する知識からファジィ論理により硬膜嚢らしさを求める.実験では, 被験者5人(健常者4人, 疾患者1人)から得られたMR画像に対して本方法を適用し, 抽出領域の3次元表示と医師による手抽出の結果との一致度から提案法の有効性を確認した.

Assessment of language dominance is one of important pre-treatments of brain surgery. The objective of this paper is to propose an estimation method of 'Laterality Index (LI)', which is a measure of language dominance, using near-infrared spectroscopy and imaging (NIRS/I) modality. The proposed method called fuzzy LI is a fuzzy-extension of the conventional estimation method (Watanabe et. al., Neuroscience Letters, 1998) called crisp LI. The benefit of our method is that the fuzzy degree belonging to language area for each measurement point is given, and that the language area is dynamically determined study by study using only NIRS/I. Experimental results on seven normal healthy right-handed volunteers showed that the fuzzy LI was correlated with one's handedness investigated by Edinburgh score at 77%.