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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 146  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
MI 2021-03-15
Online Online Comparison of Deep Learning Reconstruction for MR Compressed Sensing
Shinya Abe, Shohei Ouchi, Satoshi Ito (Utsunomiya Univ.) MI2020-56
The theory of compressed sensing (CS) has been introduced to MRI to reduce the scan time. However, CS reconstruction int... [more] MI2020-56
MI 2021-03-17
Online Online Applications of hybrid reconstruction combining PET and Compton imaging
Hideaki Tashima, Eiji Yoshida (NIRS-QST), Takumi Nishina (Chiba Univ.), Sodai Takyu, Fumihiko Nishikido (NIRS-QST), Mikio Suga (Chiba Univ.), Hidekatsu Wakizaka, Miwako Takahashi, Kotaro Nagatsu, Atsushi Tsuji (NIRS-QST), Kei Kamada, Akira Yoshikawa (C&A/Tohoku Univ.), Katia Parodi (LMU), Taiga Yamaya (NIRS-QST) MI2020-94
We have been developing WGI enabling simultaneous measurement of PET and Compton imaging. This study developed a hybrid ... [more] MI2020-94
PRMU, IPSJ-CVIM 2021-03-04
Online Online Media detection from cardiovascular OCT images based on deep learning
jiwei zhang, kai wang (wakayama univ), Takashi Kubo (Wakayama Medical Univ), haiyuan wu (wakayama univ) PRMU2020-80
Medical image segmentation is an important issue in determining whether medical images can provide reliable evidence in ... [more] PRMU2020-80
ICSS, IPSJ-SPT 2021-03-01
Online Online A Method for Reconstructing Hidden Background Image in Tele-conference with Virtual Background
Satoki Tsuji, Ryusei Ishikawa (Ritsumeikan Univ.), Masashi Eto (NICT), Yuichi Hattori (Secure Cycle Inc.), Hiroyuki Inoue (Hiroshima City Univ.) ICSS2020-35
Interpersonal communications through video chat software has become essential since a remote work is now encouraged. Whe... [more] ICSS2020-35
IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] 2021-02-18
Online Online Image Reconstruction Technique using Object's Motion for Single Photon Imaging
Kiyotaka Iwabuchi, Yusuke Kameda, Takayuki Hamamoto (TUS) ITS2020-33 IE2020-47
The single-photon imaging that enables high-quality imaging even in a low incident light level environment, records inci... [more] ITS2020-33 IE2020-47
PRMU 2020-12-18
Online Online A Hybrid Sampling Strategy for Improving the Accuracy of Image Classification with less Data
Ruiyun Zhu, Fumihiko Ino (Osaka Univ.) PRMU2020-62
This paper proposes a hybrid sampling strategy to improve learning accuracy with less training data for image classifica... [more] PRMU2020-62
ITS, IEE-ITS 2020-03-10
Shiga Ritsumeikan Univ. (BKC)
(Cancelled but technical report was issued)
A study on three-dimensional reconstruction using a scanning laser range finder and a spherical camera
Kou Yamasaki, Yasushi Tauchi, Yoshiki Mizukami (Yamaguchi Univ.) ITS2019-72
In this study, we attempt to reconstruct a 3D structure by synthesizing 3D point cloud obtained with a combination of a ... [more] ITS2019-72
- 2019-12-13
Hiroshima Hiroshima-ken Joho Plaza (Hiroshima) Moire fringe animation display by see-through cloth overlay
Kazuki Yamada, Naoto Wakatsuki, Koichi Mizutani, Keiichi Zempo (Univ. Tsukuba)
We propose a method that enables animation by overlapping see-through cloths. We use moire as a
way to make this design... [more]

MI, MICT [detail] 2019-11-05
Ibaraki Univ. of Tsukuba [Short Paper] Evaluating image quality of nonlocal total variation and nonlocal means filter based Compressed Sensing in sparse-view CT
Yongchae Kim, Katsuya Fujii, Hiroyuki Kudo (Tsukuba Univ.) MICT2019-23 MI2019-50
TV(Total Variation) is studied most widely in the field of X-ray CT image reconstruction. However, TV considers only adj... [more] MICT2019-23 MI2019-50
MI, MICT [detail] 2019-11-05
Ibaraki Univ. of Tsukuba [Short Paper] Proposal of fault-tolerant CT image reconstruction using Nonlocal Total Variation and its application to metal artifact reduction
Kazuki Chigita (Univ. Tsukuba), Jian Dong (TUTE), Yongchae Kim, Hiroyuki Kudo (Univ. Tsukuba) MICT2019-37 MI2019-64
When some abnormal data is included in the projection data, the normal image reconstruction method increases the influen... [more] MICT2019-37 MI2019-64
PRMU, MI, IPSJ-CVIM [detail] 2019-09-05
Okayama   [Short Paper] Dynamic PET Image Reconstruction using Non-Negative Matrix Decomposition with Deep Image Prior
Tomoshige Shimomura, Kazuya Kawai (NIT), Muneyuki Sakata (Tokyo Metro. Inst. Gerontology), Yuichi Kimura (KU), Tatsuya Yokota, Hidekata Hontani (NIT) PRMU2019-24 MI2019-43
We present a PET image reconstruction method that can reconstruct dynamic PET images with high SN ratio and can simultan... [more] PRMU2019-24 MI2019-43
SANE 2019-08-23
Tokyo Electric Navigation Research Institute Three-dimensional Reconstruction of Man-made Structures for Multibaseline Circular SAR Measurements
Takuma Watanabe, Daisuke Ogawa, Yasuyuki Oishi (Fujitsu) SANE2019-38
Circular synthetic aperture radar (CSAR) is a microwave imaging technique which employs a circular flight trajectory of ... [more] SANE2019-38
(Joint) [detail]
Kagoshima Kagoshima University Image quality evaluation of low contrast CT images using moving average filters
Keisuke Fujii (Nagoya Univ./NCCHE), Kuniharu Imai, Mitsuru Ikeda, Chiyo Yamauchi-Kawaura (Nagoya Univ.), Keiichi Nomura, Yoshihisa Muramatsu, Hiroyuki Ota (NCCHE) IMQ2018-60 IE2018-144 MVE2018-91
Image contrast and noise are one of important indices for evaluating image quality of low contrast CT images such as abd... [more] IMQ2018-60 IE2018-144 MVE2018-91
EA, SIP, SP 2019-03-14
Nagasaki i+Land nagasaki (Nagasaki-shi) [Poster Presentation] MR Image Reconstruction Using Two Types of Dictionaries and the Diagonalization of a BCCB Matrix
Kazuma Nakamoto, Kosuke Fujii, Daichi Kitahara, Akira Hirabayashi (Ritsumeikan Univ.) EA2018-112 SIP2018-118 SP2018-74
We propose a high-quality MR image reconstruction method using both of an adaptive orthogonal dictionary and a pre-train... [more] EA2018-112 SIP2018-118 SP2018-74
Tokyo University of Electro Communications PET Image Reconstruction by use of Dictionary Learning
Naohiro OKumura, Hayaru Shouno (UEC) NC2018-85
Nowadays, Positron Emission Tomography (PET) scan is focused in the field of pathological diagnosis.In order to obtain a... [more] NC2018-85
MBE 2019-01-31
Saga Saga University Development of a System for Visual Image Reconstruction by Decoding Brain State Using a Compact EEG Recorder
Aina Arai, Ryota Horie (SIT) MBE2018-57
In this study, we proposed a method to reconstruct images from EEG signals measured from a subject who looked at the im... [more] MBE2018-57
IBISML 2018-11-05
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Posterior mean approximation solution combining multiple image prior distributions in MR image reconstruction
Nanako Kubota, Ken Harada (Waseda Univ.), Koji Fujimoto, Tomohisa Okada (Kyoto Univ.), Masato Inoue (Waseda Univ.) IBISML2018-47
In the MR image reconstruction, combining multiple image prior distributions is preferred to obtain better results, but ... [more] IBISML2018-47
IMQ 2018-10-19
Kyoto Kyoto Institute of Technology Evaluation of Imaging Method by the Video Coding Efficiency and Its Analysis
Kenji Sugiyama, Go Kasahara (Seikei Univ.) IMQ2018-12
In color imaging, single sensor system with color filter array (CFA) is popular, especially with Bayer CFA. The improvem... [more] IMQ2018-12
NLP 2018-08-08
Kagawa Saiwai-cho Campus, Kagawa Univ. Development of Deep Neural Network for Initial Values Generation of Dynamical Image-Reconstruction System
Ken'ichi Fujimoto, Yuichi Tanji, Hiroyuki Kitajima, Yo Horikawa (Kagawa Univ.) NLP2018-56
One of the authors et al.¥ have proposed a continuous-time dynamical system for reconstructing tomographic images from a... [more] NLP2018-56
IE 2018-06-29
Okinawa   Image Coding based on Completion using Generative Adversarial Networks
Shota Orihashi, Shinobu Kudo, Masaki Kitahara, Atsushi Shimizu (NTT) IE2018-27
In this paper, we propose an image coding method applying image completion using the framework of generative adversarial... [more] IE2018-27
 Results 1 - 20 of 146  /  [Next]  
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