Details of the Researcher

PHOTO

Utako Yamamoto
Section
Graduate School of Information Sciences
Job title
Associate Professor
Degree

  • 博士（工学）（京都大学）

  • 修士（工学）（京都大学）

Research Areas 3

  • Life sciences / Medical systems /

  • Informatics / Intelligent informatics /

  • Life sciences / Biomedical engineering /

Awards 3

  1. Abe Research Award for Young Scientists

    2018/06　Japanese Society for Medical Engineering

  2. ISMRM Travel Award

    2018/03　Japanese Society for Magnetic Resonance in Medicine

  3. IFMBE Young Investigator Competition (First Prize in Poster Session)

    2011/09　The International Federation for Medical and Biological Engineering

Papers 31

  1. Spatio-temporal reconstruction of substance dynamics using compressed sensing in multi-spectral magnetic resonance spectroscopic imaging International-journal Peer-reviewed

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    Expert Systems with Applications　232　120744-120744　2023/12

    Publisher: Elsevier BV

    DOI： 10.1016/j.eswa.2023.120744 　

    ISSN： 0957-4174

  2. Kernel-based framework to estimate deformations of pneumothorax lung using relative position of anatomical landmarks International-journal Peer-reviewed

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Junko Tokuno, Toyofumi Fengshi Chen-Yoshikawa, Tetsuya Matsuda

    Expert Systems with Applications　183　115288-115288　2021/11

    DOI： 10.1016/j.eswa.2021.115288 　

    ISSN： 0957-4174

    eISSN： 1873-6793

  3. Deformation Estimation of Deflated Lung using Kernel Method based on the Relative Position of Some Landmarks Peer-reviewed

    Yamamoto Utako, Nakao Megumi, Ohzeki Masayuki, Tokuno Junko, Yoshikawa Toyofumi, Matsuda Tetsuya

    Transactions of the Institute of Systems, Control and Information Engineers　33　(4)　123-127　2020/04/10

    Publisher: THE INSTITUTE OF SYSTEMS, CONTROL AND INFORMATION ENGINEERS (ISCIE)

    DOI： 10.5687/iscie.33.123 　 10.1541/ieejjia.20012890_references_DOI_FVJft9KQ3mXYMEnECNfe40GjboW 　

    ISSN： 1342-5668

    eISSN： 2185-811X

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    It is expected to grasp how the lung deform by the deaeration during surgery compared to the inflated lung. In this study we propose a method to estimate deformation of the deflated lung from the inflated one based on the relative position of some landmarks using dog lungs. The kernel method was employed for the estimation as a machine learning technique. We achieved mean local positional error of 2.96 mm for test data where the volume reduction by the deaeration was 40 %.

  4. Improving Time Resolution in the Imaging of Metabolic Dynamics using Compressed Sensing from 3D Heteronuclear Multiple Quantum Coherence Peer-reviewed

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    Proceedings of The International Society for Magnetic Resonance in Medicine 26 (2019)　1289　2018/06

  5. Evaluating Working Memory Capacity with Functional Near-infrared Spectroscopy Measurement of Brain Activity Peer-reviewed

    Utako Yamamoto, Nozomi Mashima, Tomoyuki Hiroyasu

    Journal of Cognitive Enhancement　2　(3)　217-224　2018/01

    DOI： 10.1007/s41465-017-0063-y 　

    ISSN： 2509-3290

    eISSN： 2509-3304

  6. Fiber tracking and tractography with magnetic resonance diffusion tensor imaging for quantitative evaluation of schizophrenia

    Utako Yamamoto

    Kyoto University　2013/03

  7. Analyses of the Disruption of White Matter Integrity in Schizophrenia using Diffusion Tensor Fiber Tracking with Automatic Construction of Region of Interest Peer-reviewed

    Utako Yamamoto, Akifumi Hisada, Tetsuo Kobayashi, Shinsuke Kito, Yoshihiko Koga

    Advanced Biomedical Engineering　2　1-10　2013/01

    ISSN： 2187-5219

  8. Magnetic resonance diffusion tensor tractography by searching for minimum curvature deviation near fiber crossing area Peer-reviewed

    U. Yamamoto, Y. Sakagami, T. Oida, T. Kobayashi

    2012 ICME International Conference on Complex Medical Engineering, CME 2012 Proceedings　588-592　2012/10/24

    DOI： 10.1109/ICCME.2012.6275690 　

  9. Study on the disruption of cerebral white matter integrity in schizophrenia with MR-DTI tractography Peer-reviewed

    U. Yamamoto, Y. Kono, T. Kobayashi, S. Kito, Y. Koga

    IFMBE Proceedings　37　618-621　2011/11/09

    DOI： 10.1007/978-3-642-23508-5_160 　

    ISSN： 1680-0737

  10. A Curvature Deviation Minimization Searching Method for {MR} Diffusion Tensor Tractography Peer-reviewed

    Utako Yamamoto, Yoshihide Sakagami, Takenori Oida, Tetsuo Kobayashi

    Transactions of the Japanese Society for Medical and Biological Engineering　49　(1)　139-147　2011/02

    Publisher: Japanese Society for Medical and Biological Engineering

    DOI： 10.11239/jsmbe.49.139 　

    ISSN： 1347-443X

    eISSN： 1881-4379

  11. Analyses of disruption of cerebral white matter integrity in schizophrenia with MR diffusion tensor fiber tracking method Peer-reviewed

    Utako Yamamoto, Tetsuo Kobayashi, Shinsuke Kito, Yoshihiko Koga

    IEEJ Transactions on Electronics, Information and Systems　130　(5)　9-806　2010

    Publisher: Institute of Electrical Engineers of Japan

    DOI： 10.1541/ieejeiss.130.799 　

    ISSN： 1348-8155 0385-4221

    eISSN： 1348-8155

  12. Two-craft Coulomb-force formation dynamics and stability analysis with Debye length characteristics International-journal Peer-reviewed

    Utako Yamamoto, Hiroshi Yamakawa

    AIAA/AAS Astrodynamics Specialist Conference and Exhibit　2008

    DOI： 10.2514/6.2008-7361 　

  13. A Feature Transformation Method using Multiobjective Genetic Programming for Two-Class Classification International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Toshihide Shiraishi, Tomoya Yoshida, Utako Yamamoto

    2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)　2989-2995　2015

    DOI： 10.1109/CEC.2015.7257261 　

  14. Interactive Genetic Algorithm with Brain Activation Measured by Functional Magnetic Resonance Imaging Peer-reviewed

    Misato Tanaka, Mitsunori Miki, Utako Yamamoto, Tomoyuki Hiroyasu

    2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)　2222-2229　2015

    DOI： 10.1109/CEC.2015.7257159 　

  15. Investigation of Regions of Interest (ROI) through the Selection of Optimized Channels in fNIRS Data International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Tomoya Yoshida, Utako Yamamoto

    2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)　764-768　2015

    DOI： 10.1109/CEC.2015.7256968 　

  16. Suggestion an Algorithm Extracting Similar Parts between Two Time-series Data ―Examination for fNIRS Time-series Data Peer-reviewed

    Tomoyuki Hiroyasu, Arika Fukushima, Utako Yamamoto, Hisatake Yokouchi

    7　(2)　64-73　2014/11/27

    Publisher: Information Processing Society of Japan (IPSJ)

    ISSN： 1882-7780

    More details Close

    In this study, the algorithm, Multiple analogy Parts extracting algorithm (MaPea), is proposed. The proposed algorithm is a method to extract similar parts from two different time series data sets of cerebral blood flow using functional Near-infrared Spectroscopy (fNIRS). The MaPea can extract not only the exact similar parts but also the similar parts having a few differences. This method also extracts similar parts whose sampling numbers are different and which have time lags. In the MaPea, each two different time-series data sets of cerebral blood flow is vectorized and the similarity of these vectors are evaluated using cosine similarities. The similar parts of these two data sets are extracted using the similar method of Dynamic Programing. In the latter half of this paper, the experiment is performed and MaPea is applied to fNIRS time-series data to confirm the effectiveness of the proposed method. The results of MaPea are compared with those of t-test. The results suggest that the analysis using MaPea leads the brain activities which are occurred by the neurovascular coupling. From the results, it is suggested that MaPea is is effective for fNIRS time-series data.

  17. Improving the Accuracy of the Method for Removing Motion Artifacts from fNIRS Data using ICA and an Accelerometer Peer-reviewed

    Utako Yamamoto, Yuka Nakamura, Hisatake Yokouchi, Tomoyuki Hiroyasu

    2014 WORLD AUTOMATION CONGRESS (WAC): EMERGING TECHNOLOGIES FOR A NEW PARADIGM IN SYSTEM OF SYSTEMS ENGINEERING　131-136　2014

    DOI： 10.1109/WAC.2014.6935730 　

    ISSN： 2154-4824

    eISSN： 2154-4832

  18. Brain Activity during Cooperative Work Determined by Simultaneous fNIRS Measurement in Two People and the Effect of Different Social Skills on Cooperative Task Performance Peer-reviewed

    Utako Yamamoto, Mao Goto, Hisatake Yokouchi, Tomoyuki Hiroyasu

    2014 WORLD AUTOMATION CONGRESS (WAC): EMERGING TECHNOLOGIES FOR A NEW PARADIGM IN SYSTEM OF SYSTEMS ENGINEERING　43-47　2014

    DOI： 10.1109/WAC.2014.6935648 　

    ISSN： 2154-4824

    eISSN： 2154-4832

  19. Medical Image Management System with Automatic Image Feature Tag Adding Functions International-journal Peer-reviewed

    Tomoyuki HIROYASU, Yuji NISHIMURA, Utako YAMAMOTO

    Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems　Vol. 2　613-624　2014

    DOI： 10.1007/978-3-319-13356-0_48 　

  20. Cell Segmentation Using Binarization and Growing Neural Gas International-journal Peer-reviewed

    Tomoyuki HIROYASU, Shunsuke SEKIYA, Noriko KOIZUMI, Naoki OKUMURA, Utako YAMAMOTO

    Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems　Vol. 2　179-190　2014

    DOI： 10.1007/978-3-319-13356-0_15 　

  21. Working memory training strategies and their influence on changes in brain activity and white matter International-journal Peer-reviewed

    Tomoyuki HIROYASU, Shogo OBUCHI, Misato TANAKA, Tatsuya OKAMURA, Utako YAMAMOTO

    Proceedings of the 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems　Vol. 2　267-278　2014

    DOI： 10.1007/978-3-319-13356-0_22 　

  22. Endoscope Image Analysis Method for Evaluating the Extent of Early Gastric Cancer International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Katsutoshi Hayashinuma, Hiroshi Ichikawa, Nobuaki Yagi, Utako Yamamoto

    2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE FOR MULTIMEDIA, SIGNAL AND VISION PROCESSING (CIMSIVP)　30-34　2014

    DOI： 10.1109/CIMSIVP.2014.7013268 　

  23. A Feature Transformation Method using Genetic Programming for Two-Class Classification International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Toshihide Shiraishi, Tomoya Yoshida, Utako Yamamoto

    2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM)　234-240　2014

    DOI： 10.1109/CIDM.2014.7008673 　

  24. Gender classification of subjects from cerebral blood flow changes using Deep Learning International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Kenya Hanawa, Utako Yamamoto

    2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING (CIDM)　229-233　2014

    DOI： 10.1109/CIDM.2014.7008672 　

  25. Electroencephalographic Method Using Fast Fourier Transform Overlap Processing for Recognition of Right- or Left-handed Elbow Flexion Motor Imagery International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Yuuki Ohkubo, Utako Yamamoto

    2014 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN BRAIN COMPUTER INTERFACES (CIBCI)　24-29　2014

    DOI： 10.1109/CIBCI.2014.7007788 　

  26. Interactive recommender system to estimate personal user's Kansei models International-journal Peer-reviewed

    Misato TANAKA, Masahiro MIYAJI, Utako YAMAMOTO, Tomoyuki HIROYASU, Mitsunori MIKI

    International Journal on Computer Science and Engineering　Vol.5, No.11　(3)　904-913　2013/11

    Publisher: Engg Journals Publications

    DOI： 10.14988/pa.2017.0000013322 　

    ISSN： 0036-8172

  27. A Preliminary Study of Interaction Effects on Brain Activity during Cooperative Work using fNIRS Peer-reviewed

    Tomoyuki Hiroyasu, Mao Goto, Utako Yamamoto, Hisatake Yokouchi

    2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013)　3882-3886　2013

    DOI： 10.1109/SMC.2013.662 　

    ISSN： 1062-922X

  28. Extracting Rules for Cell Segmentation in Corneal Endothelial Cell Images using GP International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Shunsuke Sekiya, Sakito Nunokawa, Noriko Koizumi, Naoki Okumura, Utako Yamamoto

    2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013)　1811-1816　2013

    DOI： 10.1109/SMC.2013.305 　

    ISSN： 1062-922X

  29. Construction of an Interactive System Aims to Extract Expert Knowledge about the Condition Cultured Corneal Endothelial Cells Peer-reviewed

    Tomoyuki Hiroyasu, Kiyofumi Uehori, Utako Yamamoto, Misato Tanaka

    2013 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2013)　1805-1810　2013

    DOI： 10.1109/SMC.2013.312 　

    ISSN： 1062-922X

  30. Extraction Algorithm of Similar Parts from Multiple Time-Series Data of Cerebral Blood Flow International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Arika Fukushma, Utako Yamamoto

    BRAIN AND HEALTH INFORMATICS　8211　138-146　2013

    DOI： 10.1007/978-3-319-02753-1_14 　

    ISSN： 0302-9743

    eISSN： 1611-3349

  31. Analysis of Brain Areas Activated while Using Strategies to Improve the Working Memory Capacity International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Shogo Obuchi, Misato Tanaka, Utako Yamamoto

    BRAIN AND HEALTH INFORMATICS　8211　42-51　2013

    DOI： 10.1007/978-3-319-02753-1_5 　

    ISSN： 0302-9743

    eISSN： 1611-3349

Show all ︎Show first 5

Misc. 40

  1. Kernel-based framework to estimate deformations of pneumothorax lung using anatomical landmarks

    Yamamoto Utako, Nakao Megumi, Ohzeki Masayuki, Tokuno Junko, Yoshikawa Toyofumi, Matsuda Tetsuya

    Transactions of Japanese Society for Medical and Biological Engineering　Annual59　(Abstract)　515-515　2021

    Publisher: Japanese Society for Medical and Biological Engineering

    DOI： 10.11239/jsmbe.annual59.515 　

    ISSN： 1347-443X

    eISSN： 1881-4379

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    In video-assisted thoracoscopic surgeries, the precise estimation of lung deformation between the inflated lung in the computed tomography (CT) images during preoperative planning and the deflated lung in the treatment views during surgery is expected. The purpose of this study is to develop a deformation estimation method of the 3D surface of a deflated lung from a few partial observations. To estimate deformations for a largely deformed lung, a kernel regression-based solution was introduced. The proposed method used a few landmarks to capture the partial deformation between the 3D surface mesh obtained from preoperative CT and the intraoperative anatomical positions. The method was applied on nine datasets of the left lungs of live Beagle dogs. Contrast-enhanced CT images of the lungs were acquired. The proposed method achieved a local positional error of vertices of 2.74 mm, Hausdorff distance of 6.11 mm, and Dice similarity coefficient of 0.94.

  2. Deformation estimation of deflated lung using kernel method based on the relative position of some landmarks

    システム制御情報学会研究発表講演会講演論文集(CD-ROM)　63rd　472-475　2019

  3. Improvement of temporal resolution for patio-temporal reconstruction using compressed sensing in 2D 1H-13C HMQC MRSI Peer-reviewed

    38S　188　2018/09

  4. 日本生体医工学会 平成二十九年度各賞受賞者紹介

    山本 詩子

    生体医工学　56　(3)　81-86　2018/06/10

    Publisher: 公益社団法人 日本生体医工学会

    DOI： 10.11239/jsmbe.56.81 　

    ISSN： 1347-443X

    eISSN： 1881-4379

  5. Deformation estimation of an elastic object by partial observation using a neural network.

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

    arXiv　cs.CV　(1711.10157)　2017/11

    More details Close

    Deformation estimation of elastic object assuming an internal organ is important for the computer navigation of surgery. The aim of this study is to estimate the deformation of an entire three-dimensional elastic object using displacement information of very few observation points. A learning approach with a neural network was introduced to estimate the entire deformation of an object. We applied our method to two elastic objects; a rectangular parallelepiped model, and a human liver model reconstructed from computed tomography data. The average estimation error for the human liver model was 0.041 mm when the object was deformed up to 66.4 mm, from only around 3 % observations. These results indicate that the deformation of an entire elastic object can be estimated with an acceptable level of error from limited observations by applying a trained neural network to a new deformation.

  6. Time-series reconstruction using compressed sensing with ADMM in 2D magnetic resonance spectroscopic imaging

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    International Meeting on "High-Dimensional Data-Driven Science" (HD3-2017)　Poster9　2017/09

  7. Time-series Reconstruction using Compressed Sensing in 2D ^1H-^13C Heteronuclear Multiple Quantum Coherence MRSI

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    37S　423　2017/09

  8. Estimation of elastic deformation by partial observation with kernel method

    Yamamoto Utako, Nakao Megumi, Ohzeki Masayuki, Matsuda Tetsuya

    Transactions of Japanese Society for Medical and Biological Engineering　55Annual　(3AM-Abstract)　180-180　2017

    Publisher: Japanese Society for Medical and Biological Engineering

    DOI： 10.11239/jsmbe.55annual.180 　

    ISSN： 1347-443X

    eISSN： 1881-4379

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    It is expected to support surgical navigation by estimating the deformation of the whole organ from the deformation information of the partially observed organs in the surgical operation. In this study, we estimated the deformation of 3-dimensional elastic body simulated by nonlinear finite element method, assuming the situation of gripping organs with forceps and applying force to deform during endoscopic surgery. As an approach to learn deformation, we estimated the displacement based on the data using the regression with the kernel method. Kernel method allow to learn the displacement without depending on the initial value of parameters for learning and suppress learning time. In actual elastic deformation, observation can only be performed in a partial range, and the displacement of only few points can be tracked. So, we estimated displacement of whole elastic object from the displacement information of only the very few mesh vertices which were observable points.

  9. 弾性体の部分観測によるニューラルネットワークを用いた変形推定

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

    IEICE Technical Report　116　(411)　185-192　2017/01

    Publisher: 電子情報通信学会

    ISSN： 0913-5685

  10. Anatomical labeling with belief propagation in Bayes estimation for human brain

    36S　321　2016

  11. A novel fiber tracking method with MR-DTI based on curvature and torsion for crossing area of multiple nerve bundles

    YAMAMOTO Utako, HISADA Akifumi, KOBAYASHI Tetsuo

    IEICE technical report. ME and bio cybernetics　112　(479)　19-24　2013/03/13

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

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    We developed a novel method focusing on the problem caused in the performance of the fiber tracking. When multiple tracts are crossing in the white matter, the tracked fiber jumps to the adjacent untargeted bundle frequently. In the proposed method, the fiber tracking skips the unrelated tract and interpolate the trajectory in an area where we assess multiple bundles are crossing during the fiber tracking on the targeted bundle. The proposed methods were verified with the simulation data corresponding to the white matter in the human brain. The obtained simulation results demonstrate robustness of the proposed method.

  12. MR-DTIを用いた神経線維追跡による統合失調症患者の下縦束および下前頭後頭束における病変の解析と評価

    山本 詩子, 久田 祥史, 小林 哲生, 鬼頭 伸輔, 古賀 良彦

    第40回日本磁気共鳴医学会大会 講演抄録集　32.S　416　2012

  13. 統合失調症患者の下前頭後頭束における病変のMR-DTI線維追跡法を用いた解析と評価

    山本 詩子, 河野 良明, 小林 哲生, 鬼頭 伸輔, 古賀 良彦

    第39回日本磁気共鳴医学会大会講演抄録集　31.S　437　2011/10

  14. On disruption of cerebral white matter integrity in schizophrenia with MR diffusion tensor imaging : Fiber tracking of the superior longitudinal fasciculus

    ヤマモト ウタコ, コバヤシ テツオ, キトウ シンスケ

    109　(123(MBE2009 18-37))　57-62　2009/07/03

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

    eISSN： 2432-6380

  15. Discussion on estimation of preference level by neuroimaging for application of interactive optimization

    Proceedings of the Annual Conference of JSAI　JSAI2015　3F3OS19a5-3F3OS19a5　2015

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2015.0_3f3os19a5 　

    ISSN： 1347-9881

  16. テクスチャ解析を用いた内視鏡画像における早期胃癌の評価手法の検討

    林沼 勝利, 山本 詩子, 市川 寛, 八木 信明, 廣安 知之

    MEDICAL IMAGING TECHNOLOGY　33　(Suppl.)　1-6　2014/07

    Publisher: 日本医用画像工学会

    ISSN： 0288-450X

  17. 2本の時系列データの類似部分自動抽出法の提案-fNIRS時系列データに対する検討-

    廣安知之, 福島亜梨花, 山本詩子, 横内久猛

    情報処理学会研究報告. MPS, 数理モデル化と問題解決研究報告　2014　(18)　1-6　2014/02/24

    Publisher: 一般社団法人情報処理学会

    ISSN： 0919-6072

    More details Close

    2 つの異なる fNIRS 装置の脳血流時系列データから類似部分を抽出するアルゴリズム "Multipleanalogy Parts extracting algorithm (MaPea)" を提案する.MaPea では,完全一致部分だけではなく微小な差異を考慮した類似部分も抽出する.また,サンプル数の異なる類似部分を抽出することも可能にしている.脳血流時系列データが様々な要因に影響されていると報告されており,実際のデータは脳血流の活性化モデルと異なることが考えられるからである.また,時間軸上で時間差を持った類似部分の組み合わせも抽出できる.MaPea では,異なる時系列データ毎にベクトル化を行い,それらのコサイン類似度により評価する.2 つのデータセットから類似部分を動的計画法の概念を使い抽出する.MaPea の有効性を fNIRS 時系列データを使った実験により検証した.実際の fNIRS 時系列データを用いて脳機能の検定を t 検定を用いた解析手法と MaPea を用いた解析手法で行い,結果を比較した.MaPea による解析手法のほうが神経血管カップリングの理論にそって脳活動を探索できていた.以上より,MaPea が脳血流時系列データに対して有用であることが示唆された.

  18. 課題の難易度変化による成績の違いが脳活動に及ぼす影響

    杉田出弥, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　16th　2014

  19. 雑音環境下における数字記憶課題時の成績と脳血流変化に対する男女差の検討

    將積彩芽, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　16th　2014

  20. fNIRSを用いた脳の異種感覚情報処理機構についての検討

    滝謙一, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　16th　2014

  21. 専門家が良好と判断する角膜内皮細胞画像生成システム

    松浦 秀行, 上堀 聖史, 山本 詩子, 廣安 知之

    人工知能学会全国大会論文集　JSAI2014　2D12-2D12　2014

    Publisher: 一般社団法人 人工知能学会

    DOI： 10.11517/pjsai.jsai2014.0_2d12 　

    ISSN： 1347-9881

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    近年，角膜の病気に対する治療では専門家の目視によって角膜の評価が行われているが，目視による判断は専門家によって精度が異なる問題がある．よって，本研究では細胞診断における客観的評価基準の確立を目的とし，専門家が良好と判断する角膜内皮細胞画像を生成するシステムを対話型遺伝的アルゴリズムを用いて構築した．本稿では，構築したシステムの概要と専門家によるシステム評価実験の結果について述べる．

  22. fNIRSから得られる時系列データ間の相関値を特徴量とする識別の検討

    吉田 倫也, 福島 亜梨花, 山本 詩子, 廣安 知之

    人工知能学会全国大会論文集　JSAI2014　1F35-1F35　2014

    Publisher: 一般社団法人 人工知能学会

    DOI： 10.11517/pjsai.jsai2014.0_1f35 　

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    fNIRSやfMRIと行った非侵襲な装置を利用することにより、ヒトの脳機能情報を取得することが容易になってきた。これらの情報を利用することで、男女の区別やタスクに対する得意、不得意といった識別を行うことが可能である。しかしながら、どのような脳機能情報を利用するかで、識別の精度は大きく異なる。本研究では、fNIRSの各プローブで得られる時系列データ間の相関値を特徴量として識別する手法の検討を行う。

  23. A method of multiple feature construction for two symbolic classiffication problems using Genetic Programming

    Proceedings of the Annual Conference of JSAI　JSAI2014　1D32-1D32　2014

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2014.0_1d32 　

    ISSN： 1347-9881

  24. Fundamental study of the state classification of subjects with Deep Learning to cerebral blood flow changes

    Proceedings of the Annual Conference of JSAI　JSAI2014　1F5OS06b2-1F5OS06b2　2014

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2014.0_1f5os06b2 　

    ISSN： 1347-9881

  25. Classification method of elbow flexion motor imagery using Electroencephalogram

    Proceedings of the Annual Conference of JSAI　28　1-4　2014

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2014.0_1f4os06a2 　

    ISSN： 1347-9881

  26. 色温度環境が注意の持続に及ぼす影響

    大西 夏子, 田中 美里, 福島 亜梨花, 田中 美寿穂, 若村 智子, 山本 詩子, 廣安 知之

    人工知能学会全国大会論文集　2014　(0)　1F4OS06a4-1F4OS06a4　2014

    Publisher: 一般社団法人 人工知能学会

    DOI： 10.11517/pjsai.jsai2014.0_1f4os06a4 　

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    <p>本稿では，実験前の心理状態により色温度が作業時の脳活動に及ぼす影響が異なることを示す．本研究では，心理状態の評価にPOMS(Profile of Mood States)を用い，高低2種類の色温度環境下で実験を行った．脳活動の調査には，近赤外分光法を用いてGO/NOGO Task時の脳血流変化を計測した．結果として，高色温度環境下において，活気のある被験者群で課題中の脳血流の著しい増加が見られた．</p>

  27. Decision Method of Learning Region in Image-Processing GP for Cell Segmentation

    Proceedings of the Annual Conference of JSAI　2014　(0)　2D13-2D13　2014

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2014.0_2d13 　

    ISSN： 1347-9881

  28. Discussion of brain functional on the effects of color temperature on sustained attention using functional near-infrared spectroscopy International-journal Peer-reviewed

    Tomoyuki HIROYASU, Natsuko ONISHI, Misato TANAKA, Arika FUKUSHIMA, Tomoko WAKAMURA, Utako YAMAMOTO

    Neuroscience　2013/11

  29. Impact of sustained attention on difference between visual and auditory stimuli International-journal Peer-reviewed

    Tomoyuki Hiroyasu, Akane Kimura, Arika Fukushima, Misato Tanaka, Tomoko Wakamura, Utako Yamamoto

    Neuroscience, Nov　2013/11

  30. Analysis of Working Memory using the Reading Span Test: Basic Research of Regional Brain Activity on Brain Cortex using Functional Near-infrared Spectroscopy

    Tomoyuki HIROYASU, Nozomi MASHIMA, Utako YAMAMOTO

    54　(3)　240-247　2013/10

    Publisher: Science and Engineering Research Institute of Doshisha University

    DOI： 10.14988/pa.2017.0000013326 　

    ISSN： 0036-8172

  31. An MR Diffusion Tensor Imaging Study on the Disruption of Cerebral White Matter Integrity in Alzheimer's Disease : Fiber Tracing in the Cingulum

    HISADA Akifumi, YAMAMOTO Utako, KOBAYASHI Tetsuo, YAMAZAKI Takashi, NAGATA Ken

    IEICE technical report. ME and bio cybernetics　113　(61)　43-48　2013/05/17

    Publisher: The Institute of Electronics, Information and Communication Engineers

    ISSN： 0913-5685

    eISSN： 2432-6380

  32. fNIRS実験時における音圧変化の影響の検討

    井上楓彩, 星野雄地, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　15th　2013

  33. 視覚刺激と聴覚刺激の違いにおける注意の持続性への影響

    木村茜, 福島亜梨花, 若村智子, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　15th　2013

  34. 色温度環境の差異が注意の持続に及ぼす影響のfNIRSを用いた検討

    大西夏子, 福島亜梨花, 若村智子, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　15th　2013

  35. リーディングスパンテストを用いたワーキングメモリの検討-fNIRSを利用した基礎的検討-

    真島希実, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　15th　2013

  36. GO/NOGO課題の難易度変化が脳の反応抑制に与える影響の検討

    杉田出弥, 福島亜梨花, 山本詩子, 廣安知之

    日本ヒト脳機能マッピング学会プログラム・抄録集　15th　2013

  37. Discussion of interactive optimization system in Real-time fMRI

    Proceedings of the Annual Conference of JSAI　JSAI2013　3H3OS05b4-3H3OS05b4　2013

    Publisher: The Japanese Society for Artificial Intelligence

    DOI： 10.11517/pjsai.jsai2013.0_3h3os05b4 　

    ISSN： 1347-9881

  38. <学生の声>「わからないことはひとにききましょう。」

    山本 詩子

    26　62-62　2011/09

    Publisher: 京都大学電気関係教室・洛友会

    DOI： 10.14989/152122 　

    ISSN： 1882-5214

  39. Two-Craft Coulomb-Force Formation Dynamics International-journal

    YAMAKAWA Hiroshi, YAMAMOTO Utako

    Proceedings of 18th workshop on JAXA Astrodynamics and flight mechanics　18th　209-214　2009/03

  40. Satellite Formation Flight with Electromagnetic Force

    山川宏, 小嶋浩嗣, 上田善勝, 矢野克之, 向井祐利, 山本詩子

    宇宙科学技術連合講演会講演集(CD-ROM)　52nd　189　2008

    ISSN： 1884-1945

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Presentations 9

  1. Application of Q-Adam to deep neural network for deformation estimation of elastic object International-presentation

    Utako Yamamoto, Masayuki Ohzeki, Megumi Nakao, Tetsuya Matsuda

    7th Adiabatic Quantum Computing Conference 2018, AQC-18　2018/06/26

  2. Application of concept of quantum annealing to deep neural network for deformation estimation of elastic object International-presentation

    Utako Yamamoto, Masayuki Ohzeki, Megumi Nakao, Tetsuya Matsuda

    Quantum Machine Learning and Biomimetic Quantum Technologies　2018/03/19

  3. Time-series Reconstruction using Compressed Sensing in 2D 1H-13C Heteronuclear Multiple Quantum Coherence MRSI

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    The 45th Annual Meeting of the Japanese Society of Magnetic Resonance in Medicine　2017/09/14

  4. Time-series reconstruction using compressed sensing with ADMM in 3D magnetic resonance spectroscopic imaging International-presentation

    Utako Yamamoto, Hirohiko Imai, Kei Sano, Masayuki Ohzeki, Tetsuya Matsuda, Toshiyuki Tanaka

    International Meeting on High-Dimensional Data-Driven Science (HD3-2018)　2017/09/12

  5. Estimation of elastic deformation by partial observation with kernel method

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

    The 56th conference of the Japanese Society for Medical and Biological Engineering　2017/05/03

  6. Shape estimation of elastic object with neural network International-presentation Invited

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

    Workshop on Statistical Physics of Disordered Systems and Its Applications, SPDSA2017　2017/02/08

  7. ヒトの臓器を模した弾性体の変形シミュレーションへの機械学習の応用 Invited

    Utako Yamamoto, Megumi Nakao, Masayuki Ohzeki, Tetsuya Matsuda

    第一回 構造イメージングと情報処理研究会　2017/02/07

  8. 拡散テンソル画像法を用いたファイバートラッキングについて

    Utako Yamamoto

    Seminer at the Integrated Systems Biology Laboratory in Department of Systems Science, Kyoto University　2016/12/27

  9. Anatomical labeling with belief propagation in Bayes estimation for human brain

    Utako Yamamoto, Masayuki Ohzeki, Tomoyuki Hiroyasu, Megumi Nakao, Tetsuya Matsuda

    The 44th Annual Meeting of the Japanese Society of Magnetic Resonance in Medicine　2016/09/11

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Research Projects 8

  1. ブラックボックス最適化を用いた臓器の変形推定手法の開発

    山本 詩子

    Offer Organization: 日本学術振興会

    System: 科学研究費助成事業 基盤研究(C)

    Category: 基盤研究(C)

    Institution: 京都大学

    2022/04/01 - 2025/03/31

  2. Development of next generation MRI measurement method using combinatorial optimization technique with quantum annealing

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research Grant-in-Aid for JSPS Fellows

    Category: Grant-in-Aid for JSPS Fellows

    Institution: Kyoto University

    2020/04/24 - 2023/03/31

  3. Medical image interpretation support system based on appearance transformation of images

    Offer Organization: Japan Society for the Promotion of Science

    System: Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists

    Category: Grant-in-Aid for Early-Career Scientists

    Institution: Kyoto University

    2019/04/01 - 2022/03/31

  4. 脱気変形肺に対応した微小結節の術中同定法

    伊達洋至, 陳豊史, 濱路政嗣, 松田哲也, 中尾恵, 山本詩子, 武淑瓊, 石井隆司, 長坂学, 乾谷徹, 片岡弘之, 高波健太郎、坂本英男

    Offer Organization: 国立研究開発法人日本医療研究開発機構

    System: 医療分野研究成果展開事業

    Institution: 京都大学

    2017/04 - 2020/03

  5. 生体画像の統計的性質と医師の叡智を統合した脳疾患自動検出技術の開発 Competitive

    Utako Yamamoto

    Offer Organization: Japan Society for the Promotion of Science (JSPS)

    System: KAKENHI, Grant-in-Aid for Young Scientists (B)

    Category: Grant-in-Aid for Young Scientists (B)

    Institution: Kyoto University

    2016/04 - 2019/03

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    We integrate the statistical characteristics of human brain MRI images and the radiologist’s knowledge about the clinical images to support the interpretation of radiogram. The MR diffusion tensor images which had multiple kinds of contrast were employed as feature vectors. Label maps which were classified to anatomical regions by a radiologist were utilized as supervised label. We developed the labeling technique for brain MRI images based on the Bayesian inference and Boltzmann machine learning. And we developed the reconstruction method of biomedical spectroscopic data obtained by MRI using sparse modeling technique. We made research presentations and discussed about these results in some research conferences by The Japanese Society for Magnetic Resonance in Medicine, The International Society for Magnetic Resonance in Medicine, etc.

  6. ヒト脳画像の統計的性質を用いた脳疾患自動検出技術の開発 Competitive

    Utako Yamamoto

    Offer Organization: Kyoto University

    System: The Kyoto University Research Funds for Young Scientists (Step-up)

    2015/04 - 2016/03

  7. 脳内情報処理の時空間定量解析 複数刺激の時間差入力に対する脳血行動態と神経結合 Competitive

    Utako Yamamoto

    Offer Organization: Japan Society for the Promotion of Science (JSPS)

    System: KAKENHI, Grant-in-Aid for Research Activity Start-up

    Category: Grant-in-Aid for Research Activity Start-up

    Institution: Doshisha University

    2013/04 - 2015/03

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    Our purpose of this study was to analyze dynamic brain information processing mechanism concerned with the time series processing of multiple input. We observed spatiotemporal interrelation of the brain activity to process information from multiple sensory irritation and the brain nerve fibers’ structure to connect active cortical areas. We measured the brain activity responding to visual and auditory stimuli individually or simultaneously by functional near-infrared spectroscopy (fNIRS). The three dimensional structure of the nerve fibers was constructed with the data set by the magnetic resonance diffusion tensor imaging (MR-DTI) method. The temporal waveform reflecting the brain activity obtained from fNIRS optodes were resampled in each voxel of brain cortex measured by magnetic resonance imaging method. We observed the time variation of relationship between the brain activation in voxel units and the nerve fibers passing through the activated voxels.

  8. 精神疾患の定量評価 診断支援システムに向けた拡散テンソルMRI計測と神経線維追跡 Competitive

    Utako Yamamoto

    Offer Organization: Japan Society for the Promotion of Science (JSPS)

    System: KAKENHI, Grant-in-Aid for JSPS Research Fellow (DC2)

    2011/04 - 2013/03

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