Image Processing Research Team

Team Leader

Hideo Yokota

D.Eng.

Hideo Yokota

Contact

Access map

brict [at] riken.jp

Image Processing Research Team,
RIKEN Center for Advanced Photonics

2-1 Hirosawa, Wako, Saitama 351-0198 Japan

Related links

Outline

Our goal is to develop original RIKEN data processing technology and multidimensional measurement technology in order to contribute to understanding biological phenomena. We are especially contributing to the fields of mathematical biology, bio-medical simulations as well as medical diagnostic and treatment technology by researching and developing new data and image processing technologies and establishing new tools for quantification of biological phenomena, intended for researchers both inside and outside RIKEN.

Fields

Engineering, Informatics

Keywords

Multi dimensional image processing, Multi dimensional imaging, Bioengineering, Image analysis, Medical engineering

Subjects

  1. Development of algorithms for image processing
  2. Development of image processing systems
  3. Construction of instrumentation system for bio-research data creation
Image Processing Cloud

Image Processing Cloud

Selected Publications

  1. R. Sakaguchi, T. Shiraiwa, P. Chivavibul, T.Kasuya, M. Enoki, N. Yamashita, H. Yokota, Y.Matsui, A. Kazama, K. Ozaki, H. Takamatsu.:”Multiscale Analysis of MnS Inclusion Distributions in High Strength Steel”, ISIJ International.10.2355/isijinternational. ISIJINT-2019-739 (2020).
  2. S. Kudo, H.Yokota, M. Akiba, M. Mandai, Y.Hirami, M. Takahashi, Y. Kurimoto, M. Ishida.:“Assessment of the deformation of the outer nuclear layer in the Epiretinal membrane using spectral-domain optical coherence tomography” , BMC Ophthalmology 2019, 19:113 (2019).
  3. N. Motozawa, G. An, S. Takagi, S. Kitahata, M. Mandai, Y. Hirami, H. Yokota, M. Akiba, A. Tsujikawa, M. Takahashi, Y. Kurimoto.:“Optical Coherence Tomography-Based Deep-Learning Models for Classifying Normal and Age-Related Macular Degeneration and Exudative and Non-Exudative Age-Related Macular Degeneration Changes” , Ophthalmology and Therapy, 8, pages527–539 (2019).
  4. T. Kitrungrotsakul, X.-H. Han, Y. Iwamoto, S. Takemoto, H. Yokota, S. Ipponjima, T. Nemoto, W. Xiong & Y.-W. Chen.:“An end-to-end CNN and LSTM network with 3D anchors for mitotic cell detection in 4D microscopic images and its parallel implementation on multiple GPUs” , Neural Computing and Applications, doi:10.1007/s00521-019-04374-8 (2019).
  5. K. Ayabe, S. Goto, H. Oka, H. Yabushita, M. Nakayama, A. Tomita, T. Hasebe, H. Yokota, S. Takagi, S. Goto.:“Potential different impact of inhibition of thrombin function and thrombin generation rate for the growth of thrombi formed at site of endothelial injury under blood flow condition” , Thrombosis Research, 179, PP.121-127, July (2019).

Members

Hideo YokotaTeam Leader
Shin YoshizawaSenior Scientist
Satoshi OotaSenior Research Scientist
Shigeho NodaSenior Scientist
Takashi MichikawaSenior Scientist
Satoko TakemotoResearch Scientist
Masahiko MoritaResearch Scientist
Norio YamashitaResearch Scientist
Zhe SunResearch Scientist
Sakiko NakamuraTechnical StaffⅠ
Yuki TsujimuraTechnical StaffⅠ
Masaomi NishimuraTechnical StaffⅠ
Yoshimasa SakaiTechnical Staff II
Xianping ZhangJRA