Paper Abstract and Keywords |
Presentation |
2018-06-13 15:50
3D Super Resolution Microscopy using Convolutional Neural Network Masaru Tanaka (Waseda Univ.), Hideitsu Hino (ISM), Shigeyuki Namiki, Daisuke Asanuma, Kenzo Hirose (The Univ. of Tokyo), Noboru Murata (Waseda Univ.) IBISML2018-11 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Super-resolution microscopy is a microscopy technique with a resolution beyond the diffraction limit of light. Despite the recent advancement, there are no techniques for real-time visualization of 3D structures. Using Convolutional Neural Network which has received much attention in the field of image recognition in recent years, we developed a 3D Super-resolution method. We confirmed the proposed method can visualize 3D structures in real time with 20~nm resolution. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
3D Super-resolution microscopy / Convolutional Neural Network / Single Molecule Fluorescence / Sparse Coding / Live Imaging / Multiplane Imaging / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 81, IBISML2018-11, pp. 75-80, June 2018. |
Paper # |
IBISML2018-11 |
Date of Issue |
2018-06-06 (IBISML) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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IBISML2018-11 |