Kyushu University Academic Staff Educational and Research Activities Database
Search by Keyword How ro search
Keyword
Search Criteria
 
Detailed Search

Researcher information (To researchers) Need Help? How to update
Shoko Miyauchi Last modified date：2023.09.29

Assistant Professor / Real World Robotics
Department of Advanced Information Technology
Faculty of Information Science and Electrical Engineering


Graduate School
Department of Advanced information Technology
Graduate School of Information Science and Electrical Engineering
Undergraduate School
Department of Electrical Engineering and Computer Science
School of Engineering


E-Mail　*Since the e-mail address is not displayed in Internet Explorer, please use another web browser:Google Chrome, safari.
Homepage
https://kyushu-u.elsevierpure.com/en/persons/shoko-miyauchi
　Reseacher Profiling Tool　Kyushu University Pure
https://researchmap.jp/s_miyauchi
Phone
092-802-3605
Fax
092-802-3607
Academic Degree
Ph.D (Eng.)
Country of degree conferring institution (Overseas)
No
Field of Specialization
Medical Image Processing
Total Priod of education and research career in the foreign country
00years03months
Research
Research Interests
  • Construction of Denoising & Mesher DNN for 3D object recognition
    keyword : 3D object recognition, Deep learning
    2019.10～2022.03.
  • Construction of Multi-dimensional Statistical Shape Model for a heart
    keyword : Statistical Shape Model
    2018.10～2020.03.
  • Mapping of human organ models onto target spaces for the systematization of human organs
    keyword : Medical images, Surface model, Volumetric model, Statistical shape model
    2012.04～2018.05.
  • Innovative Computer-Aided Cancer Diagnosis with Artificial Intelligence using Cell Shape and Appearance
    keyword : cancer diagnosis, cell classification
    2017.10～2023.03.
Academic Activities
Reports
 Show All Reports >>
Papers
 Show All Papers >>
1. Kurazume, Tomoki Hiramatsu, Masaya Kamei, Daiji Inoue, Akihiro Kawamura, Shoko Miyauchi, and Qi An, Development of AR training systems for Humanitude dementia care, 10.1080/01691864.2021.2017342, 2022.01.
2. Junichi Inokuchi, Fumio Kinoshita, Yoshinao Oda, Masatoshi Eto, Ryo Kurazume, Ken'ichi Morooka, Jun Mutaguchi, Satoshi Kobayashi, Shoko Miyauchi, Aiko Umehara, Artificial intelligence for segmentation of bladder tumor cystoscopic images performed by U-Net with dilated convolution, 10.1089/end.2021.0483, 2022.01.
3. Fumiaki Ichihashi, Akira Koyama, Tetsuya Akashi, Shoko Miyauchi, Ken'ichi Morooka, Hajime Hojo, Hisahiro Einaga, Yoshio Takahashi, Toshiaki Tanigaki, Hiroyuki Shinada, Yasukazu Murakami, Automatic electron hologram acquisition of catalyst nanoparticles using particle detection with image processing and machine learning, Applied Physics Letters, 10.1063/5.0074231, 120, 6, 1-6, 2022.02, To enable better statistical analysis of catalyst nanoparticles by high-resolution electron holography, we improved the particle detection accuracy of our previously developed automated hologram acquisition system by using an image classifier trained with machine learning. The detection accuracy of 83% was achieved with the small training data of just 232 images showing nanoparticles by utilizing transfer learning based on VGG16 to train the image classifier. Although the construction of training data generally requires much effort, the time needed to select the training data candidates was significantly shortened by utilizing a pattern matching technique. Experimental results showed that the high-resolution hologram acquisition efficiency was improved by factors of about 100 and 6 compared to a scan method and a pattern-matching-only method, respectively..
4. Ken’ichi Morooka, Ryota Matsubara, Shoko Miyauchi, Takaichi Fukuda, Takeshi Sugii, Ryo Kurazume, Ancient pelvis reconstruction from collapsed component bones using statistical shape models, Machine Vision and Applications, 59-69, 2019.02.
5. Shoko Miyauchi, Ken'ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Fast modified Self-organizing Deformable Model: Geometrical feature-preserving mapping of organ models onto target surfaces with various shapes and topologies, Computer Methods and Programs in Biomedicine, 157, 237-250, 2018.01.
Presentations
 Show All Presentations >>
1. Shoko Miyauchi, Ken'ichi Morooka, Tokuo Tsuji, Yasushi Miyagi, Takaichi Fukuda, Ryo Kurazume, Angle- and Volume-Preserving Mapping of Organ Volume Model Based on modified Self-organizing Deformable Model, 23rd International Conference on Pattern Recognition (ICPR 2016), 2016.12.
Membership in Academic Society
  • IEEE
Educational
Other Educational Activities
  • 2019.09.


Unauthorized reprint of the contents of this database is prohibited.

Copyright © 2006, Kyushu University. All rights reserved.