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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 113  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
17:00
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Deformable registration of 3D medical images with Deep Residual UNet
Taiga Nakamura, Yuki Sato, Hiroyuki Kudo, Hotaka Takizawa (Univ. of Tsukuba) SIP2022-30 BioX2022-30 IE2022-30 MI2022-30
(To be available after the conference date) [more] SIP2022-30 BioX2022-30 IE2022-30 MI2022-30
pp.156-160
MI 2022-01-26
13:39
Online Online Deep Learning based 2D/3D deformable Image Registration for Abdominal Organs
Ryuto Miura, Megumi Nakao, Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MI2021-62
2D/3D image registration is a problem that solves the deformation and alignment of a pre-treatment 3D image to a 2D proj... [more] MI2021-62
pp.70-75
MI 2022-01-26
14:05
Online Online [Short Paper] Joint Learning for Multi-Phase CT Image Registration and Automatic Recognition of Anatomical Structures Based on a Deep Neural Network
Ryotaro Fuwa, Xiangrong Zhou, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2021-64
Computer-aided diagnosis (CAD) systems require image registration and automatic recognition of anatomical structures on ... [more] MI2021-64
pp.82-85
MI 2021-03-16
16:15
Online Online Pre-operative Head CT and Pathological Image Registration using Normalized Cross-Correlation and Dice coefficient
Yukinobu Matsuoka, Kento Morita (Mie Univ.), Daisuke Takeda, Takumi Hasegawa (Kobe Univ. Hospital), Tetsushi Wakabayashi (Mie Univ.) MI2020-81
The radiation therapy to oral cancer sometimes causes the osteoradionecrosis of jaws which is know as a refractory disea... [more] MI2020-81
pp.144-149
MI 2021-03-17
10:45
Online Online [Short Paper] Preliminary study for improving the performance of abdominal multi-phase CT image registration based on 3D deep CNN with a CycleGAN
Ryotaro Fuwa, Xiangong Zhou, Takeshi Hara, Hiroshi Fujita (Gifu Univ.) MI2020-90
Deep learning is expected to be an approach to solve the problem of accurate medical image alignment. Recently, VoxelMor... [more] MI2020-90
pp.182-185
LOIS, EMM, IE, IEE-CMN, ITE-ME, IPSJ-AVM [detail] 2020-09-01
17:20
Online Online Study on automatic label masking method for plant specimen images using CTPN
Depeng Zhang, Yasuhiko Higaki, Yasuo Sugai (Chiba Univ.) LOIS2020-8 IE2020-20 EMM2020-32
In this study, the image processing required for registration of the Haginiwa plant specimen image database in c-arc. Si... [more] LOIS2020-8 IE2020-20 EMM2020-32
pp.19-24
IE, IMQ, MVE, CQ
(Joint) [detail]
2020-03-05
17:05
Fukuoka Kyushu Institute of Technology
(Cancelled but technical report was issued)
[Invited Talk] Image Registration Method for Comparative Reading
Hyoungseop Kim, Huimin Lu (KIT), Takatoshi Aoki (UOEH), Shoji Kido (Osaka Univ) IMQ2019-28 CQ2019-134 IE2019-110 MVE2019-49
Image registration techniques are used not only medical fields but also in various fields such as positioning problems o... [more] IMQ2019-28 CQ2019-134 IE2019-110 MVE2019-49
pp.69-72(IMQ), pp.1-4(CQ), pp.69-72(IE), pp.69-72(MVE)
IMQ, IE, MVE, CQ
(Joint) [detail]
2019-03-14
17:10
Kagoshima Kagoshima University [Invited Talk] Pattern Optimization Using Evolutionary Computation
Satoshi Ono (Kagoshima Univ.) IMQ2018-51 IE2018-135 MVE2018-82
This study focuses Evolutionary Computation (EC) that is a black-box optimization framework for non-differentiable, glob... [more] IMQ2018-51 IE2018-135 MVE2018-82
pp.165-171
IBISML 2018-11-05
15:10
Hokkaido Hokkaido Citizens Activites Center (Kaderu 2.7) [Poster Presentation] Development of the topology-preserving image alignment based on a local deformation of kernel density function
Masataka Watajima (KIT), Sayuri Kuge, Takeshi Ishihara (KU), Yuichi Iino (UT), Ryo Yoshida (ISM), Terumasa Tokunaga (KIT) IBISML2018-55
Image alignment or image registration is a process for aligning two or more images into a common coordinate system. Many... [more] IBISML2018-55
pp.83-90
PRMU, IBISML, IPSJ-CVIM [detail] 2018-09-21
13:50
Fukuoka   Multi-modal image registration based on local mutual information
Hiroaki Tani, Toshikazu Wada (Wakayama Univ) PRMU2018-65 IBISML2018-42
In recent years, various types of images having different modality from visible-light images, such as infrared images, d... [more] PRMU2018-65 IBISML2018-42
pp.207-212
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
10:05
Okinawa   A preliminary study on unsupervised registration with deep learning
Kai Nagara, Holger R. Roth, Shota Nakamura, Masahiro Oda, Kensaku Mori (Nagoya Univ.) MI2017-65
Registration is one of the important processes in medical image processing. Many researchers have proposed methods for r... [more] MI2017-65
pp.7-12
SIP, EA, SP, MI
(Joint) [detail]
2018-03-19
10:20
Okinawa   Automatic extraction of ultrasonic measurement area from pathological image for registration with ultrasonic image
Maho Funato, Takashi Ohnishi, Shu Kashio, Kazuyo Ito, Tadashi Yamaguchi, Yasuo Iwadate, Hideaki Haneishi (Chiba Univ.) MI2017-66
We have been developing the registration between the pathological image and ultrasonic image by a scanning acoustic micr... [more] MI2017-66
pp.13-16
MBE, BioX 2017-07-29
13:25
Tokushima Tokushima University Personal Authentication Using Iris Images Captured Under Visible Light Condition
Kouki Hongo, Hironobu Takano, Kiyomi Nakamura (Toyama Prefectural Univ.) BioX2017-16 MBE2017-25
In this study, we proposed the personal authentication method using an iris image captured under the visible light envir... [more] BioX2017-16 MBE2017-25
pp.37-41
MI 2017-07-06
16:15
Miyagi Tohoku Univ. An Automated Method for Generating Training Data for Image Registration Using Deep Learning
Masato Ito, Fumihiko Ino, Kenichi Hagihara (Osaka Univ.) MI2017-28
In this paper, we propose an automated method for generating training data that realizes image registration with deep le... [more] MI2017-28
pp.11-16
MBE, NC
(Joint)
2017-05-26
15:45
Toyama Toyama Prefectural Univ. A 2D/3D registration method developed for superposing an MRI-reconstructed bone model on a set of bi-directional CR images
Takuya Kaneta, Toyohiko Hayashi (Niigata Univ.), Satoshi Watanabe (Niigata Medical Center), Yoshio Koga (Ninohji hot), Go Omori (Niigata Univ. of Health and Welfare) MBE2017-8
The lower extremity alignment of the lower extremity in the standing position has been evaluated by computed radiography... [more] MBE2017-8
pp.39-44
PRMU, IE, MI, SIP 2016-05-20
15:40
Aichi   Highly Accurate Reconstruction of Microscope 3D images based on Micro Anatomic Structures
Hirokazu Kobayashi, Hidekata Hontani (NIT) SIP2016-29 IE2016-29 PRMU2016-29 MI2016-29
The objective of this research is to develop a method for accurately
registering 2D microscope images of spatially succ... [more]
SIP2016-29 IE2016-29 PRMU2016-29 MI2016-29
pp.153-156
ITS, IE, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] 2016-02-23
11:45
Hokkaido Hokkaido Univ. Satellite Image Registration Based on Minimization of Distance between Panchromatic Image and Synthesized Image from Multispectral Images
Momoyo Nagase, Hideaki Maehara, Shunichi Sekiguchi (Mitsubishi Electric Corp.) ITS2015-80 IE2015-122
Satellites have both panchromatic sensors and multispectral sensors. Pansharpen is a multisensory fusion technique which... [more] ITS2015-80 IE2015-122
pp.265-268
PRMU, CNR 2016-02-22
11:00
Fukuoka   Development of an Indirect Augmented Reality System with Motion Parallax
Yuya Nishizaki, Tomokazu Sato (NAIST), Humio Okura (Osaka Univ.), Norihiko Kawai, Naokazu Yokoya (NAIST) PRMU2015-152 CNR2015-53
In mobile Augmented Reality (AR) applications using a smartphone, the geometric registration to accurately place virtual... [more] PRMU2015-152 CNR2015-53
pp.109-114
MI 2016-01-20
15:05
Okinawa Bunka Tenbusu Kan Highly accurate registration between pathological image and optical macro image by improving capture mechanism
Yuka Nakamura, Takashi Ohnishi, Takuya Tanaka, Hideaki Haneishi (Chiba Univ.) MI2015-141
In order to conduct multi modal and multi scale analysis, highly accurate image registration is needed. However, convent... [more] MI2015-141
pp.337-340
MI 2016-01-20
15:17
Okinawa Bunka Tenbusu Kan Texture analysis based image registration between pathological images and MR image
Takashi Ohnishi, Takuya Tanaka, Yuka Nakamura (Chiba Univ.), Nobuhiro Nitta, Ichio Aoki (NIRS), Hideaki Haneishi (Chiba Univ.) MI2015-142
Multi-scale analysis using several modalities of medical image has been conducted. In order to compare the features of i... [more] MI2015-142
pp.341-344
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