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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 66  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
16:00
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection
Daisuke Shigemori, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-27 BioX2022-27 IE2022-27 MI2022-27
Although deep learning-based image transformation has been attempted to be applied to metal artifact reduction, feature ... [more] SIP2022-27 BioX2022-27 IE2022-27 MI2022-27
pp.138-143
SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] 2022-05-20
16:20
Kumamoto Kumamoto University Kurokami Campus
(Primary: On-site, Secondary: Online)
Visualization of Important Features for Classifier Decisions using Deep Image Synthesis
Yushi Haku, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-28 BioX2022-28 IE2022-28 MI2022-28
It is difficult to know the basis for the decisions of machine learning models, and it is necessary to provide a highly ... [more] SIP2022-28 BioX2022-28 IE2022-28 MI2022-28
pp.144-149
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, MICT [detail] 2021-11-05
09:00
Online Online Deformable model registration for a single projection image by learning displacement fields
Megumi Nakao, Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MICT2021-27 MI2021-25
(To be available after the conference date) [more] MICT2021-27 MI2021-25
pp.1-6
MI, MICT [detail] 2021-11-05
09:20
Online Online Force estimation in forceps manipulation of ex-vivo organs from a single-viewpoint camera image
Hikaru Toda, Megumi Nakao, Kimihiko Masui, Naoto Kume, Tetsuya Matsuda (Kyoto Univ.) MICT2021-28 MI2021-26
In laparoscopic surgery including robotic surgery, it is not possible to accurately measure the contact force applied to... [more] MICT2021-28 MI2021-26
pp.7-12
MI 2021-03-15
13:45
Online Online Surgical planning model generation by extracting important feature sets in mandibular reconstruction
Kazuki Nagai, Megumi Nakao (Kyoto Univ.), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Rakuwakai Otowa Hospital), Toshihide Hatanaka, Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2020-54
Because implicit medical knowledge and experience are used to perform medical treatment, such decisions must be clarifie... [more] MI2020-54
pp.29-34
MI 2021-03-15
14:00
Online Online Analysis of important features in surgical planning for mandibular reconstruction among multiple surgeons
Yusuke Hatakeyama, Kazuki Nagai, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) MI2020-55
Surgeons perform surgical treatment by considering the facilities and policies of medical institutions and their own exp... [more] MI2020-55
pp.35-40
MI 2021-03-16
14:00
Online Online Deformable mesh registration of partial lung shapes based on learning of pneumothorax deformation
Hinako Maekawa, Megumi Nakao (Kyoto Univ.), Katsutaka Mineura (Kyoto Univ. Hospital), Toyofumi F. Chen-Yoshikawa (Nagoya Univ. Hospital), Tetsuya Matsuda (Kyoto Univ.) MI2020-74
Intraoperative pneumothorax is accompanied by large deformation including rotation. As intraoperative cone-beam CT (CBCT... [more] MI2020-74
pp.112-117
MI 2020-09-03
10:00
Online Online Lung region segmentation of thoracoscopic image with unsupervised image translation
Jumpei Nitta, Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth Co. Ltd.), Tetsuya Matsuda (Kyoto Univ.) MI2020-19
In endoscopic surgery, it is necessary to understand the three-dimensional structure of the target region to improve saf... [more] MI2020-19
pp.13-18
MI 2020-09-03
14:10
Online Online Reconstruction of 3D Organ Shape from a Single X-ray Image using Graph Convolutional Network
Fei Tong, Megumi Nakao (Kyoto Univ.), Shuqiong Wu (Osaka Univ.), Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MI2020-28
 [more] MI2020-28
pp.45-50
MI 2020-09-03
14:25
Online Online Proposal of 3D Generative Adversarial Network for Improving Image Ouality of Cone-Beam CT Images
Takumi Hase, Megumi Nakao (Kyoto Univ.), Keoho Imanishi (e-Growth Co., Ltd), Mitsuhiro Nakamura, Tetsuya Matsuda (Kyoto Univ.) MI2020-29
Artifacts and defects included in Cone-beam CT (CBCT) images have become an obstacle in radiation therapy and surgery su... [more] MI2020-29
pp.51-56
MI 2020-09-03
14:40
Online Online Analysis of pneumothorax deformation for in vivo animal lungs using model-based registration
Kotaro Kobayashi, Megumi Nakao, Junko Tokuno (Kyoto Univ.), Toyofumi F Chen-Yoshikawa (Nagoya Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2020-30
(To be available after the conference date) [more] MI2020-30
pp.57-62
NC, MBE
(Joint)
2020-03-06
14:15
Tokyo University of Electro Communications
(Cancelled but technical report was issued)
Identification of pick and grasp manipulation based on fingertip force and velocity
Tatsuya Yamashita, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) MBE2019-98
Finger manipulation plays an important role in daily life, and the importance of its analysis is increasing in a variety... [more] MBE2019-98
pp.91-96
MI 2020-01-29
10:45
Okinawa OKINAWAKEN SEINENKAIKAN Proposal of Extraction Method of Important Features in Surgical Planning for Mandibular Reconstruction
Kazuki Nagai, Megumi Nakao (Kyoto Univ.), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Rakuwakai Otowa Hospital), Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2019-70
As implicit medical knowledge and experience are used to perform medical treatment, clarification of decision making is ... [more] MI2019-70
pp.23-28
MI 2020-01-29
11:05
Okinawa OKINAWAKEN SEINENKAIKAN A preliminary study on deformation analysis of collapsed lung using intraoperative CBCT images
Hinako Maekawa, Megumi Nakao (Kyoto Univ.), Katsutaka Mineura (Kyoto Univ. Hospital), Toyofumi F Chen-Yoshikawa (Nagoya Univ. Hospital), Tetsuya Matsuda (Kyoto Univ.) MI2019-72
 [more] MI2019-72
pp.31-36
MI 2020-01-30
10:40
Okinawa OKINAWAKEN SEINENKAIKAN Evaluation of 3D adversarial networks for metallic dental artifact reduction
Megumi Nakao (Kyoto Univ.), Keiho Imanishi (e-Growth), Nobuhiro Ueda (Nara Medical Univ.), Yuichiro Imai (Otowa Hosp.), Tadaaki Kirita (Nara Medical Univ.), Tetsuya Matsuda (Kyoto Univ.) MI2019-101
(To be available after the conference date) [more] MI2019-101
pp.159-164
PRMU, MI, IPSJ-CVIM [detail] 2019-09-04
15:55
Okayama   Analysis of pneumothorax deformation for in vivo animal lungs using model-based registration
Kotaro Kobayashi, Megumi Nakao (Kyoto Univ.), Junko Tokuno, Toyofumi F. Chen-Yoshikawa, Hiroshi Date (Kyoto Univ. Hospital), Tetsuya Matsuda (Kyoto Univ.) PRMU2019-17 MI2019-36
 [more] PRMU2019-17 MI2019-36
pp.31-36
PRMU, MI, IPSJ-CVIM [detail] 2019-09-05
10:20
Okayama   Metal artifact reduction using CycleGAN for CT images
Megumi Nakao (Kyoto Univ.), Kieho Imanishi (e-Grwoth), Nobuhiro Ueda (Nara Med.), Yuichiro Imai (Otowa Hosp.), Tadaaki Kirita (Nara Med.), Tetsuya Matsuda (Kyoto Univ.) PRMU2019-23 MI2019-42
(To be available after the conference date) [more] PRMU2019-23 MI2019-42
pp.63-68
SIP, MI, IE 2019-05-24
14:00
Aichi   Analysis of deaeration deformation for ex vivo animal lung
Kotaro Kobayashi, Megumi Nakao, Junko Tokuno, Toyofumi F. Chen-Yoshikawa, Hiroshi Date, Tetsuya Matsuda (Kyoto Univ.) SIP2019-12 IE2019-12 MI2019-12
Recent advance of imaging techniques enables to visualize minute lung nodules in the early stage cancer. Although lung n... [more] SIP2019-12 IE2019-12 MI2019-12
pp.53-58
NC, MBE
(Joint)
2019-03-04
16:10
Tokyo University of Electro Communications Relational analysis on contact force of multiple fingers during grasping object
Hideki Shimobayashi, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) MBE2018-92
Among human-object interactions, it is important to understand how to grasp objects by human hand. Many researchers trie... [more] MBE2018-92
pp.37-42
 Results 1 - 20 of 66  /  [Next]  
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