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Two-dimensional self-assembly of melem and melemium cations at pH-controlled aqueous solution-Au（111） interfaces under electrochemical control

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Frontiers of Chemical Science and Engineering 2016年第2期10卷 294-300页

作者： shinobu uemura Kenki Sakata Masashi Aono Yusuke Nakamura Masashi Kunitake Department of Advanced Materials Sciences Faculty of Engineering Kagawa University Kagawa 761-0396 Japan Graduate School of Science and Technology Kumamoto University Kumamoto 860-8555 Japan

Two-dimensional self-assembly of melem at pH-controlled aqueous solution-Au（111） interfaces has been investigated by electrochemical scanning tunneling microscopy. In the solutions with pH 〉 pKbl of melem, two ordered self-assembled structures （honeycomb and close-packed structures） and one disordered fibrillar structure were observed as a function of the surface coverage ofmelem controlled by the electrode potential. In contrast, in the acidic solution with pH 〈 pKbl of melem, only the self-assembled honeycomb network was observed in a relatively wide potential range probably due to the presence of monoprotonated melem cations. Dots attrib- uted to counteranions were frequently observed in the pores of the honeycomb network. The lack of close-packed and fibrillar structures at low pH （〈 pKbl） is attributed to ionic repulsion of melemium cations.

关键词： self-assembly scanning tunneling micro-scopy electrochemistry structural phase transition melem

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Automatic Anomaly Detection of Respiratory Motion Based on Singular Spectrum Analysis

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International Journal of Medical Physics, Clinical Engineering and Radiation Oncology 2016年第1期5卷 88-95页

作者： Jun’ichi Kotoku shinobu Kumagai Ryouhei uemura Susumu Nakabayashi Takenori Kobayashi Graduate School of Medical Technology Teikyo University Tokyo Japan Central of Radiology Teikyo University Hospital Tokyo Japan

The realization of automatic anomaly detection of respiratory motion could be very useful to prevent accidental damage during radiation therapy. In this paper, we proposed an automatic anomaly detection method using singular value decomposition analysis. Before applying this method, the investigator needs a normal respiratory motion data of a patient. From these data, a trajectory matrix representing normal time-series feature is created. Decomposing the matrix, we obtained the feature of normal time series. Then, we applied the same procedure to real-time data and obtained real-time features. Calculating the similarity of those feature matrixes, an anomaly score was obtained. Patient motion was observed by a depth camera. In our simulation, two types of motion e.g. cough and sudden stop of breathing were successfully detected, while gradual change of respiratory cycle frequency was not detected clearly.

关键词： Anomaly Detection Respiratory Motion Singular Spectrum Analysis

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Markerless Respiratory Motion Tracking Using Single Depth Camera

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Open Journal of Medical Imaging 2016年第1期6卷 20-31页

作者： shinobu Kumagai Ryohei uemura Toru Ishibashi Susumu Nakabayashi Norikazu Arai Takenori Kobayashi Jun’ichi Kotoku Graduate School of Medical Technology Teikyo University Tokyo Japan Central of Radiology Teikyo University Hospital Tokyo Japan

The aim of this study is to propose a novel system that has an ability to detect intra-fractional motion during radiotherapy treatment in real-time using three-dimensional surface taken by a depth camera, Microsoft Kinect v1. Our approach introduces three new aspects for three-dimensional surface tracking in radiotherapy treatment. The first aspect is a new algorithm for noise reduction of depth values. Ueda’s algorithm was implemented and enabling a fast least square regression of depth values. The second aspect is an application for detection of patient’s motion at multiple points in thracoabdominal regions. The third aspect is an estimation of three-dimensional surface from multiple depth values. For evaluation of noise reduction by Ueda’s algorithm, two respiratory patterns are measured by the Kinect as well as a laser range meter. The resulting cross correlation coefficients between the laser range meter and the Kinect were 0.982 for abdominal respiration and 0.995 for breath holding. Moreover, the mean cross correlation coefficients between the signals of our system and the signals of Anzai with respect to participant’s respiratory motion were 0.90 for thoracic respiration and 0.93 for abdominal respiration, respectively. These results proved that the performance of the developed system was comparable to existing motion monitoring devices. Reconstruction of three-dimensional surface also enabled us to detect the irregular motion and breathing arrest by comparing the averaged depth with predefined threshold values.

关键词： Depth Camera Markerless Motion Tracking Intra-Fractional Motion Three-Dimensional Surface

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