KUGLER Mauricio

写真a

Affiliation Department

Department of Computer Science
Department of Computer Science

Title

Assistant Professor

External Link

Degree

  • Doctor of Philosophy ( 2007.03   Nagoya Institute of Technology )

From School

  • Federal Technological University of Parana   Faculty of Engineering   Department of Electronics   Graduated

    - 2001.02

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    Country:Brazil

From Graduate School

  • Nagoya Institute of Technology   Graduate School, Division of Information Engineering   Doctor's Course   Completed

    - 2007.03

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    Country:Japan

  • Federal Technological University of Paraná   Graduate School, Division of Engineering   Master's Course   Completed

    - 2003.02

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    Country:Brazil

External Career

  • ESIGELEC   Graduate School of Engineering   Lecturer

    2014.03 - 2014.04

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    Country:France

  • ESIGELEC   Graduate School of Engineering   Lecturer

    2013.11

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    Country:France

  • ESIGELEC   Graduate School of Engineering   Lecturer

    2013.05

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    Country:France

  • ESIGELEC   Graduate School of Engineering   Lecturer

    2012.11 - 2012.12

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    Country:France

  • ESIGELEC   Gradiate School of Engineering   Lecturer

    2012.05

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    Country:France

Professional Memberships

  • 日本神経回路学会第22回全国大会実行委員会

    2011.09 - 2012.09

  • Institute of Electrical and Electronics Engineers (IEEE)

    2005.01 - 2014.04

 

Papers

  • Robust 3D image reconstruction of pancreatic cancer tumors from histopathological images with different stains and its quantitative performance evaluation Reviewed

    Mauricio Kugler, Yushi Goto, Yuki Tamura, Naoki Kawamura, Hirokazu Kobayashi, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Akinobu Shimizu, Hidekata Hontani

    International Journal of Computer Assisted Radiology and Surgery   14 ( 12 )   2047 - 2055   2019.07

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Springer  

    Purpose: Histopathological imaging is widely used for the analysis and diagnosis of multiple diseases. Several methods have been proposed for the 3D reconstruction of pathological images, captured from thin sections of a given specimen, which get non-linearly deformed due to the preparation process. The majority of the available methods for registering such images use the degree of matching of adjacent images as the criteria for registration, which can result in unnatural deformations of the anatomical structures. Moreover, most methods assume that the same staining is used for all images, when in fact multiple staining is usually applied in order to enhance different structures in the images.
    Methods: This paper proposes a non-rigid 3D reconstruction method based on the assumption that internal structures on the original tissue must be smooth and continuous. Landmarks are detected along anatomical structures using template matching based on normalized cross-correlation (NCC), forming jagged shape trajectories that traverse several slices. The registration process smooths out these trajectories and deforms the images accordingly. Artifacts are automatically handled by using the confidence of the NCC in order to reject unreliable landmarks.
    Results: The proposed method was applied to a large series of histological sections from the pancreas of a KPC mouse. Some portions were dyed primarily with HE stain, while others were dyed alternately with HE, CK19, MT and Ki67 stains. A new evaluation method is proposed to quantitatively evaluate the smoothness and isotropy of the obtained reconstructions, both for single and multiple staining.
    Conclusions: Experimental results show that the proposed method produces smooth and nearly isotropic 3D reconstructions of pathological images with either single or multiple stains. From these reconstructions, micro-anatomical structures enhanced by different stains can be simultaneously observed.

    DOI: 10.1007/s11548-019-02019-8

    Other Link: https://doi.org/10.1007/s11548-019-02019-8

  • Accurate 3D reconstruction of a whole pancreatic cancer tumor from pathology images with different stains Reviewed International journal

    Mauricio Kugler, Yushi Goto, Naoki Kawamura, Hirokazu Kobayashi, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani

    Proceedings of the 1st Workshop in Computational Pathology - 21st International Conference on Medical Image Computing & Computer Assisted Intervention   LNCS11039   35 - 43   2018.09

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    Authorship:Lead author   Language:English   Publishing type:Research paper (international conference proceedings)  

    When applied to 3D image reconstruction, conventional landmark-based registration methods tend to generate unnatural vertical structures due to inconsistencies between the employed model and the real tissue. This paper demonstrates a fully non-rigid image registration method for 3D image reconstruction which considers the spatial continuity and smoothness of each constituent part of the microstructures in the tissue. Corresponding landmarks are detected along the images, defining a set of trajectories, which are smoothed out in order to define a diffeomorphic mapping. The resulting reconstructed 3D image preserves the original tissue architecture, allowing the observation of fine details and structures.

    DOI: 10.1007/978-3-030-00949-6_5

  • Spatiotemporal information integration model of pancreatic cancer and human embryo Reviewed

    Hidekata Hontani, Mauricio Kugler, Akinobu Shimizu

    The CELL   50 ( 1 )   5 - 8   2018.01

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

  • Design of a compact sound localization device on a stand-alone FPGA-based platform Reviewed International coauthorship International journal

    IEICE Transactions on Information & Systems   E99-D ( 11 )   2682 - 2693   2016.11

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:The Institute of Electronics, Information and Communication Engineers  

    DOI: 10.1587/transinf.2015EDP7488

    Other Link: http://search.ieice.org/bin/summary.php?id=e99-d_11_2682&category=D&year=2016&lang=E&abst=

  • Real-time hardware implementation of a sound recognition system with in-field learning Reviewed International coauthorship International journal

    Mauricio Kugler, Teemu Tossavainen, Miku Nakatsu, Susumu Kuroyanagi, Akira Iwata

    電子情報通信学会論文誌   E99-D ( 7 )   1885 - 1894   2016.07

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    Authorship:Lead author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:電子情報通信学会  

    The development of assistive devices for automated sound recognition is an important field of research and has been receiving increased attention. However, there are still very few methods specifically developed for identifying environmental sounds. The majority of the existing approaches try to adapt speech recognition techniques for the task, usually incurring high computational complexity. This paper proposes a sound recognition method dedicated to environmental sounds, designed with its main focus on embedded applications. The pre-processing stage is loosely based on the human hearing system, while a robust set of binary features permits a simple k-NN classifier to be used. This gives the system the capability of in-field learning, by which new sounds can be simply added to the reference set in real-time, greatly improving its usability. The system was implemented in an FPGA based platform, developed in-house specifically for this application. The design of the proposed method took into consideration several restrictions imposed by the hardware, such as limited computing power and memory, and supports up to 12 reference sounds of around 5.3 s each. Experimental results were performed in a database of 29 sounds. Sensitivity and specificity were evaluated over several random subsets of these signals. The obtained values for sensitivity and specificity, without additional noise, were, respectively, 0.957 and 0.918. With the addition of +6 dB of pink noise, sensitivity and specificity were 0.822 and 0.942, respectively. The in-field learning strategy presented no significant change in sensitivity and a total decrease of 5.4% in specificity when progressively increasing the number of reference sounds from 1 to 9 under noisy conditions. The minimal signal-to-noise ration required by the prototype to correctly recognize sounds was between -8 dB and 3 dB. These results show that the proposed method and implementation have great potential for several real life applications.

    DOI: 10.1587/transinf.2015EDP7432

    Other Link: http://search.ieice.org/bin/summary.php?id=e99-d_7_1885&category=D&year=2016&lang=E&abst=

  • Combined Methodology for Linear Time Series Forecasting Reviewed International journal

    Ricardo Moraes Muniz da Silva, Mauricio Kugler, Taizo Umezaki

    電気学会論文誌C(電子・情報・システム部門誌)   15 ( 12 )   1780 - 1790   2020.10

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    Language:English   Publishing type:Research paper (scientific journal)   Publisher:一般社団法人 電気学会  

    Time series forecasting is an important type of quantitative model used to predict future values given a series of past observations for which the generation process is unknown. Two of the most well‐known methods for the modeling of linear time series are the autoregressive integrated moving average (ARIMA) and the autoregressive fractionally integrated moving average (ARFIMA). For different datasets, the number of past observations necessary for an accurate prediction may vary. Short and long memory dependency problems require different handling, with the ARIMA model being limited to the first, while the ARFIMA model was specifically developed for the latter. Preprocessing techniques and modification on specific components of these models are common approaches used to tackle the memory dependency problem in order to improve their accuracy. However, such solutions are specific to certain datasets. This paper proposes a new method that combines the short and long memory characteristics of the two aforementioned models in order to keep a low accumulative error in several different scenarios. Twelve public time series datasets were used to compare the performance of the proposed method with the original models. The results were also compared with two alternative methods from the literature used to deal with datasets of different memory dependencies. The new approach presented a lower error for the majority of the experiments, failing only for the datasets that contain a large number of features.

    DOI: https://doi.org/10.1002/tee.23252

    Other Link: https://onlinelibrary.wiley.com/doi/full/10.1002/tee.23252

  • Elderly Watching System based BLE Beacon and LPWA Communication Reviewed

    Akira Iwata, Jianqing Wang, Shun Shiramatsu, Masatoki Suto, Mauricio Kugler, Nobuhiko Wagatsuma

    Journal of The Society of Instrument and Control Engineers   58 ( 2 )   109 - 114   2019.02

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    Language:Japanese   Publishing type:Research paper (scientific journal)  

    DOI: 10.11499/sicejl.58.109

    Other Link: https://www.jstage.jst.go.jp/article/sicejl/58/2/58_109/_article/-char/en

  • Registration between histopathological images with different stains and an MRI Image of Pancreatic Cancer Tumor Reviewed International journal

    Hidekata Hontani, Yushi Goto, Yuki Tamura, Tomoshige Shimomura, Naoki Kawamura, Hirokazu Kobayashi, Mauricio Kugler, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Takahiro Katagiri, Tomonari Sei, Akinobu Shimizu

    Proceedings of the International Forum on Medical Imaging in Asia IFMIA2019   2019.01

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    In this paper, we report on the construction of a pancreatic tumor model that represents the relationship between the tumor growth and the micro anatomical structures. The former, the tumor growth, is described by referring to the temporal series of MRI images of the whole body and the latter, the micro structures of the tumor, is described by a spatial series of microscopic images of thin-sections sliced from the extracted pancreatic tumor. For the model construction, we developed new non-rigid registration methods for (1) accurate description of tumor growth, (2) reconstruction of 3D microscopic images, and (3) registration between an MRI image and corresponding microscopic images. In addition, we constructed a neural network that can generate a set of fake microscopic image patches of a pancreatic tumor that corresponds to each voxel inside the tumor region in an MRI image. The outlines of the methods are introduced and some examples of experimental results are demonstrated.

  • Partial rigid diffeomorphism for measuring temporal change of pancreatic cancer tumor Reviewed International journal

    Yuki Tamura, Tatsuya Yokota, Mauricio Kugler, Valentin Triquet, Tomonari Sei, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani

    Proceedings of the International Forum on Medical Imaging in Asia IFMIA2019   2019.01

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    Language:English   Publishing type:Research paper (international conference proceedings)  

  • Construction of multimodal 3D model of pancreatic cancer tumor Reviewed International journal

    Yushi Goto, Mauricio Kugler, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani

    Proceedings of the International Forum on Medical Imaging in Asia IFMIA2019   2019.01

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    Language:English   Publishing type:Research paper (international conference proceedings)  

    Histopathological imaging and Magnetic Resonance (MR) are two equally important yet very distinct modalities of medical imaging. The high resolution of the first and the non-invasiveness of the later provide complementary information for medical diagnosis and research. Due to their largely different resolutions, the registration between 3D images of these two modalities is challenging. The objective of this paper is to create a multimodal 3D model of pancreatic cancer tumor by performing the registration of a reconstructed 3D pathological image and an MR image from a KPC mouse. The tumor portions were manually segmented and the 3D pathological image was reconstructed using landmark-based non-linear registration. The process starts by registering the outline of the images using the LDDMM non-linear registration method to match the binary labels of the tumor regions. Next, a non-linear B-spline deformation method based on mutual information maximization is used to register the internal structures of the images. Experimental results show that the overall shape of the tumor and its internal necrosis portion could be correctly registered, although the quality of the manual segmentations affects the accuracy of the registration.

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Presentations

  • Construction of a Multi-modal Model of Pancreatic Tumors by Integration of MRI and Pathological Images using Conditional Cycle alpha-GAN International conference

    Tomoshige Shimomura, Mauricio Kugler, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Hidekata Hontani

    ICCV Workshop for Multi-Discipline Approach for Learning Concepts (MDALC) 

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    Event date: 2019.10 - 2019.11

    Language:English   Presentation type:Oral presentation (general)  

  • Construction of multimodal 3D model of pancreatic cancer tumor International conference

    Yushi Goto, Mauricio Kugler

    International Forum on Medical Imaging in Asia - IFMIA2019 

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    Event date: 2019.01

    Language:English   Presentation type:Poster presentation  

    Venue:Nanyang Technological University  

    Histopathological imaging and Magnetic Resonance (MR) are two equally important yet very distinct modalities of medical imaging. The high resolution of the first and the non-invasiveness of the later provide complementary information for medical diagnosis and research. Due to their largely different resolutions, the registration between 3D images of these two modalities is challenging. The objective of this paper is to create a multimodal 3D model of pancreatic cancer tumor by performing the registration of a reconstructed 3D pathological image and an MR image from a KPC mouse. The tumor portions were manually segmented and the 3D pathological image was reconstructed using landmark-based non-linear registration. The process starts by registering the outline of the images using the LDDMM non-linear registration method to match the binary labels of the tumor regions. Next, a non-linear B-spline deformation method based on mutual information maximization is used to register the internal structures of the images. Experimental results show that the overall shape of the tumor and its internal necrosis portion could be correctly registered, although the quality of the manual segmentations affects the accuracy of the registration.

  • Partial rigid diffeomorphism for measuring temporal change of pancreatic cancer tumor International conference

    Yuki Tamura, Mauricio Kugler

    International Forum on Medical Imaging in Asia - IFMIA2019 

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    Event date: 2019.01

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Nanyang Technological University  

  • Registration between histopathological images with different stains and an MRI Image of Pancreatic Cancer Tumor International conference

    Hidekata Hontani, Yushi Goto, Yuki Tamura, Tomoshige Shimomura, Naoki Kawamura, Hirokazu Kobayashi, Mauricio Kugler, Tatsuya Yokota, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, Takahiro Katagiri, Tomonari Sei, Akinobu Shimizu

    International Forum on Medical Imaging in Asia - IFMIA2019 

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    Event date: 2019.01

    Language:English   Presentation type:Oral presentation (general)  

  • Workshop in Computational Pathology - Accurate 3D reconstruction of a whole pancreatic cancer tumor from pathology images with different stains International conference

    Mauricio Kugler

    21st International Conference on Medical Image Computing & Computer Assisted Intervention 

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    Event date: 2018.09

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Granada, Spain  

    When applied to 3D image reconstruction, conventional landmark-based registration methods tend to generate unnatural vertical structures due to inconsistencies between the employed model and the real tissue. This paper demonstrates a fully non-rigid image registration method for 3D image reconstruction which considers the spatial continuity and smoothness of each constituent part of the microstructures in the tissue. Corresponding landmarks are detected along the images, defining a set of trajectories, which are smoothed out in order to define a diffeomorphic mapping. The resulting reconstructed 3D image preserves the original tissue architecture, allowing the observation of fine details and structures.

  • Workshop in Computational Pathology - Construction of a Generative Model of H&E Stained Pathology Images of Pancreas Tumors Conditioned by a Voxel Value of MRI Image International conference

    Tomoshige Shimomura, Mauricio Kugler

    21st International Conference on Medical Image Computing & Computer Assisted Intervention 

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    Event date: 2018.09

    Language:English   Presentation type:Poster presentation  

    Venue:Granada, Spain  

    In this paper, we propose a method for constructing a multiscale model of pancreas tumor of a KrasLSL.G12D/+; p53R172H/+; PdxCretg/+ (KPC) mouse that is a genetically engineered mouse model of pancreas tumor. The model represents the correlation between the value at each voxel in the MRI image of the tumor and the pathology image patches that are observed at each portion corresponds to the location of the voxel in the MRI image. The model is represented by a cascade of image generators trained by a Laplacian Pyramid of Generative Adversarial Network (LAPGAN). When some voxel in a pancreas tumor region in an MRI image is selected, the cascade of generators outputs patches of the pathology images that can be observed at the location corresponds to the selected voxel. We trained the generators by using an MRI image and a 3D pathology image, the latter was first reconstructed from a spatial series of the 2D pathology images and was then registered to the MRI image.

  • Construction of multi-scale spatiotemporal model of pancreas tumor from pathology images and time series MR images International conference

    TRIQUET, V., KUGLER, M., KOBAYASHI, H., YOKOTA, T., IWAMOTO, C., OUCHIDA, K., HASHIZUME, M., HONTANI, H.

    31st International Congress on Computer Assisted Radiology and Surgery 

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    Event date: 2017.06

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Barcelona, Spain  

  • The Impact of Memory Dependency on Precision Forecast - An Analysis on Different Types of Time Series Databases International conference

    Ricardo Moraes Muniz da Silva

    6th International Conference on Pattern Recognition Application and Methods 

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    Event date: 2017.02

    Language:English   Presentation type:Poster presentation  

    Venue:Porto, Portugal  

    Time series forecasting is an important type of quantitative method in which past observations of a set of variables are used to develop a model describing their relationship. The Autoregressive Integrated Moving Average (ARIMA) model is a commonly used method for modelling time series. It is applied when the data show evidence of nonstationarity, which is removed by applying an initial differencing step. Alternatively, for time series in which the long-run average decays more slowly than an exponential decay, the Autoregressive Fractionally Integrated Moving Average (ARFIMA) model is used. One important issue on time series forecasting is known as the short and long memory dependency, which corresponds to how much past history is necessary in order to make a better prediction. It is not always clear if a process is stationary or what is the influence of the past samples on the future value, and thus, which of the two models, is the best choice for a given time series. The objective o f this research is to have a better understanding this dependency for an accurate prediction. Several datasets of different contexts were processed using both models, and the prediction accuracy and memory dependency were compared.

  • Design and Performance Evaluation of Wearable BLE Antenna for a Localization System of Aged Wanderer International conference

    Yuto Shimizu, Shun Hiyama, Daisuke Anzai, Mauricio Kugler, Akira Iwata, Jianqing Wang

    IEEE International Conference on Biomedical and Health Informatics 

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    Event date: 2017.02

    Language:English   Presentation type:Oral presentation (general)  

  • Wearable sound localization assistive device for the hearing impaired International conference

    Mauricio Kugler

    25th Brazilian Congress on Biomedical Engineering  Brazilian Society of Biomedical Engineering

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    Event date: 2016.10

    Language:English   Presentation type:Poster presentation  

    Venue:Foz do Iguaçu, Brazil  

    The sense of hearing can provide immediate information about remote events, even when outside of the field of vision and beyond obstacles, facilitating functioning in uncontrolled environments. Hearing impairment can thus have a huge disabling effect on an individual. This paper proposes a wearable self-contained dedicated device capable of full-plane sound localization. The system, shaped as a glass frame, uses only four microphones spaced by 10 mm, and is initially targeted at a resolution of 45°. The individual binaural angles are calculated by a process loosely based on the human hearing system. These angles are then combined in order to determine the final direction. A prototype of the proposed system was implemented using 3D printing and MEMS microphones. Experiments with the prototype in a reverberant environment show an error of 6.73° when it is tested standalone and 21.16° when tested in a dummy head.

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Industrial Property Rights

  • Soft-stop function in abnormal situations for a transcranial direct-current stimulation device

    Masaharu Segawa, Seiji Onishi, Toshiyuki Takagaki, Mauricio Kugler

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    Application no:2018-3014  Date applied:2018.01

    Announcement no:2019-122429  Date announced:2019.07

    Country of applicant:Domestic   Country of acquisition:Domestic

  • Head Mounted Display

    Masatoki Suto, Mauricio Kugler, Fukaya Shousuke, Jana Makovníková

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    Applicant:Nagoya Institute of Technology

    Application no:2015-12863  Date applied:2015

    Announcement no:2016-139881  Date announced:2016

    Country of applicant:Domestic   Country of acquisition:Domestic

  • Sound source identification method and sound source identification device

    Akira Iwata, Mauricio Kugler

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    Applicant:Nagoya Institute of Technology

    Application no:2008-250360  Date applied:2008.09

    Announcement no:2010-079188  Date announced:2010.04

    Country of applicant:Domestic   Country of acquisition:Domestic

Other research activities

  • Development of a Wearable Brain Stimulation Device for Gait Rehabilitation

    2013.04 - 2015.03

  • Sound recognition & visualization using a head mount display

    2013.04 - 2014.03

  • Sound Watcher: hardware and software development for a consumer product.

    2011.01

Awards

  • Best APNNA Paper Award

    2008.11   International Neural Network Society   A Back-Propagation Training Method for Multilayer Pulsed Neural Network using Principle of Duality

    Kaname Iwasa, Mauricio Kugler, Susumu Kuroyanagi, Akira Iwata

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    Award type:Award from international society, conference, symposium, etc.  Country:New Zealand

Scientific Research Funds Acquisition Results

  • 膵癌腫瘍3次元内部構造の徹底的な理解のための超高精細情報空間構築

    2018.04 - 2021.03

    科学研究費補助金  基盤研究(B)

    本谷 秀堅、片桐 孝洋, Mauricio Kugler, 横田 達也

  • Wearable Brain Stimulation Device for Gait Rehabilitation

    2013.04 - 2015.03

    Grant-in-Aid for Scientific Research  Grant-in-Aid for challenging Exploratory Research

    Satoshi Tanaka

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    This project's main objective is to develop a wearable device that generates the necessary electrical stimulation during such sessions, being wirelessly controlled by the operator by the means of a smartphone or a tablet computer. The hardware device has to generate a constant DC current through the scalp of the subject, independently of its resistance. It has to be light and small, able to be fixed on the back of the head of the subject.

  • Visualization of sound using head-mounted display

    2011.04 - 2014.03

    Grant-in-Aid for Scientific Research  Grant-in-Aid for Scientific Research(C)

    Masatoki Suto

  • 聴覚障がい者のための音源認識・音源定位装置に関する研究

    2010 - 2012

    科学研究費補助金  基盤研究(C)

    岩田彰、Mauricio Kugler

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    聴覚情報処理モデルをFPGA(Field Programmable Gate Array)にインプリメントし、本方式による聴覚情報処理のリアルタイム化を実現した。ピンクノイズ60db状態でSN比0dB程度でも音認識できることとなった。

Other External Funds

  • 近距離通信センサの受信距離拡張と位置情報推測技術の実現によるスマートフォンを活用した認知症高齢者見守り機構の研究開発

    2015 - 2017

    総務省  総務省 

    Mauricio Kugler、岩田 彰, 小竹 暢隆, 須藤 正時

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    Grant type:Competitive

    BLEの利点である低消費電力を活かし,充電不要で使い捨てができる小型・軽量のセンサを実現するために,回折特性を向上し,電波の回り込み,伝搬距離を伸ばす.また,センサの電界強度から測定したセンサと受信機間の距離とスマートフォンの位置情報からセンサの位置を推定する測位技術を研究・開発する.本認知症高齢者見守り機構は,愛知県大府市,名古屋市中川区での社会実験を通して,社会での有用性を評価し,実用可能性を検証する.

Past of Cooperative Research

  • Study of fatigue failure prediction by acoustic signals in die-cast molds

    2020.08 - 2020.11

    Meiwa Co. Ltd.  Collaboration in Japan 

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    Authorship:Coinvestigator(s) 

  • リハビリ併用型t-DCS装置の開発

    2016.11 - 2019.10

    オージー技研株式会社  Collaboration in Japan 

    高垣 俊之、田中 悟志

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    Authorship:Principal investigator 

 

Committee Memberships

  • 日本神経回路学会第22回全国大会実行委員会   実行委員  

    2011.09 - 2012.09   

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    Committee type:Other