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Technical Committee on Medical Imaging (MI) (Searched in: 2018)
Search Results: Keywords 'from:2019-01-22 to:2019-01-22'
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2019-01-22 13:20 |
Okinawa | Cell image segmentation by Attention module Yuki Hiramatsu, Kazuhiro Hotta (Meijo Univ.)  MI2018-79 |
(To be available after the conference date) [more] | MI2018-79 pp.77-80 |
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| MI | 2019-01-22 14:20 |
Okinawa | Consideration of Influence of Identification Result which occur Individual Difference of Manual Cutting for Disease part of Oral Image in Oral Mucosal Disease Diagnosis Support System Nanto Ozaki (KIT), Taishi Ohtani, Manabu Habu, Kazuhiro Tominaga (KDC), Keiichi Horio (KIT) MI2018-80 |
Oral mucosa disease is more likely to cause various disorders after treatment to occur in the special domain called the ... [more] | MI2018-80 pp.81-86 |
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| MI | 2019-01-22 14:35 |
Okinawa | Research on macular analysis based on OCT angiography image analysis Shinnosuke Yamaoka, Shinya Fukumoto, Masayuki Kashima, Kiminori Sato, Mutsumi Watanabe, Hideki Shiihara, Syozo Sonoda, Taiji Sakamoto (Kagoshima Univ.) MI2018-81 |
The purpose of this study is to ascertain whether the complexity of the shape of macular region obtained from OCT angiog... [more] | MI2018-81 pp.87-92 |
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| MI | 2019-01-22 14:50 |
Okinawa | [Short Paper]
Towards Annotating Less Medical Images:
-- PGGAN-based MR Image Augmentation for Brain Tumor Detection -- Changhee Han (UTokyo), Hideaki Hayashi (Kyushu Univ.), Leonardo Rundo (Univ. Cambridge), Ryosuke Araki (Chubu Univ.), Yudai Nagano (UTokyo), Yujiro Furukawa (Kanto Rosai Hosp.), Giancarlo Mauri (Univ. Milano-Bicocca), Hideki Nakayama (UTokyo) MI2018-82 |
How can we tackle the lack of available annotated medical image data through Data Augmentation (DA) techniques for accur... [more] | MI2018-82 pp.93-94 |
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| MI | 2019-01-22 15:05 |
Okinawa | [Short Paper]
Study on subtype classification of malignant lymphoma using immunostaining information Noriaki Hashimoto, Kaho Ko, Daisuke Fukushima, Tatsuya Yokota (Nagoya Inst. of Tech.), Masato Nakaguro, Kei Kohno, Shigeo Nakamura (Nagoya Univ. Hospital), Ichiro Takeuchi (Nagoya Inst. of Tech./RIKEN/NIMS), Hidekata Hontani (Nagoya Inst. of Tech.) MI2018-83 |
[more] | MI2018-83 pp.95-96 |
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| MI | 2019-01-22 15:20 |
Okinawa | A Study on Automated Lymph Node Matching Method Considering Abdominal Organs Deformation in Follow-up CT Volumes Tachi Koki, Masahiro Oda, Yuichiro Hayashi, Hayato Itoh (Nagoya Univ.), Yoshihiko Nakamura (TNT), Takayuki Kitasaka (AIT), Kazunari Misawa (ACC), Kensaku Mori (Nagoya Univ.) MI2018-84 |
In this paper, we report on an automated lymph node matching method considering deformation of abdominal organs in follo... [more] | MI2018-84 pp.97-102 |
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| MI | 2019-01-22 15:35 |
Okinawa | Segmentation of lung nodules on 3D CT images by using DeconvNet and V-Net Shunsuke Kidera, Shoji Kido, Yasushi Hirano (Yamaguchi Univ.), Nobuyuki Tanaka (Saiseikai Hosp) MI2018-85 |
Semantic segmentation of lung nodules is important for texture analysis． However， manual segmentation needs a lot of tim... [more] | MI2018-85 pp.103-106 |
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| MI | 2019-01-22 16:00 |
Okinawa | [Fellow Memorial Lecture]
Recognition of organs and lesions from medical images Akinobu Shimizu (TUAT) MI2018-86 |
(To be available after the conference date) [more] | MI2018-86 p.107 |
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| MI | 2019-01-23 09:45 |
Okinawa | Feature Selection from Imbalanced Data
-- Pathological Pattern Classification in Endocytoscopic Images -- Hayato Itoh (Nagoya Univ.), Yuichi Mori, Masashi Misawa (Showa Univ.), Masahiro Oda (Nagoya Univ.), Shin-Ei Kudo (Showa Univ.), Kensaku Mori (Nagoya Univ.) MI2018-87 |
Endocytoscope gives ultramagnified observation that enables physicians to achieve minimally invasive and real-time diagn... [more] | MI2018-87 pp.109-114 |
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| MI | 2019-01-23 10:00 |
Okinawa | MI2018-88 |
(To be available after the conference date) [more] | MI2018-88 pp.115-120 |
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| MI | 2019-01-23 10:15 |
Okinawa | MI2018-89 |
[more] | MI2018-89 pp.121-126 |
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| MI | 2019-01-23 10:30 |
Okinawa | [Short Paper]
Investigation on Versatility of Automatic Detection of Microaneurysms in Retinal Image by Using Deep Learning Mitsuhiro Miyashita, Yuji Hatanaka, Kazunori Ogohara (Univ. of Shiga Pref), Chisako Muramatsu (Gifu Univ), Wataru Sunayama (Univ. of Shiga Pref), Hiroshi Fujita (Gifu Univ) MI2018-90 |
(To be available after the conference date) [more] | MI2018-90 pp.127-129 |
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| MI | 2019-01-23 10:55 |
Okinawa | Semi-Automated Segmentation of Rotator Cuff in MR Images with Statistical Shape Model Kazuki Ishiro, Kento Morita, Manabu Nii (Univ. of Hyogo), Tomoyuki Muto, Hiroshi Tanaka, Hiroaki Inui (Nobuhara Hospital), Syoji Kobashi (Univ. of Hyogo), Katsuya Nobuhara (Nobuhara Hospital) MI2018-91 |
A surgical method to repair rotator cuff tear is decided by a tear form. To diagnose the tear form, we previously propos... [more] | MI2018-91 pp.131-136 |
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| MI | 2019-01-23 11:10 |
Okinawa | [Short Paper]
Improvement of a liver segmentation algorithm from a pediatric CT volume
-- Simultaneous optimization of a shape prior by a conditional statistical shape model and segmentation -- Koyo Nakayama, Atsushi Saito (TUAT), Elijah Biggs, Marius George Linguraru (Children's National), Akinobu Shimizu (TUAT) MI2018-92 |
(To be available after the conference date) [more] | MI2018-92 pp.137-138 |
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| MI | 2019-01-23 11:25 |
Okinawa | Musculoskeletal Segmentation of Metal Artifact-Reduced Maxillofacial CT Images Yuka Moritani, Fatemeh Abdolali, Mitsuki Sakamoto, Yoshito Otake (NAIST), Yuko Shigeta, Tomoko Ikawa, Akira Mishima, Takumi Ogawa (Tsurumi Univ.), Yoshinobu Sato (NAIST) MI2018-93 |
[more] | MI2018-93 pp.139-142 |
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| MI | 2019-01-23 11:40 |
Okinawa | Influence of group normalization in multi-class organ segmentation of abdominal CT volumes Chen Shen (Nagoya Univ.), Fausto Milletari, Holger R. Roth (Nvidia), Hirohisa Oda, Masahiro Oda, Yuichiro Hayashi (Nagoya Univ.), Kazunari Misawa (Aichi Cancer Center Hospital), Kensaku Mori (Nagoya Univ.) MI2018-94 |
Organ segmentation is one of the most important branches of medical image analysis. Fully convolutional networks (FCNs) ... [more] | MI2018-94 pp.143-148 |
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| MI | 2019-01-23 11:55 |
Okinawa | [Short Paper]
Construction and evaluation of a statistical model of an organ using Variational Autoencoder Zhihui Lu, Atsushi Saito (TUAT), Shigeru Nawano (IUHW), Junji Ueno, Masafumi Harada (Tokushima Univ.), Akinobu Shimizu (TUAT) MI2018-95 |
(To be available after the conference date) [more] | MI2018-95 pp.149-150 |
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| MI | 2019-01-23 14:00 |
Okinawa | Unsupervised Shadow Detection for Ultrasound Images by Deep Learning Suguru Yasutomi (FLL), Akira Sakai (FATEC), Masaaki Komatsu (Riken), Ryu Matsuoka, Reina Komatsu, Tatsuya Arakaki, Mayumi Tokunaka (Showa-U), Hidenori Machino, Kazuma Kobayashi (NCC), Ken Asada (Riken), Syuzo Kaneko (NCC), Akihiko Sekizawa (Showa-U), Ryuji Hamamoto (Riken) MI2018-96 |
Medical ultrasound is widely used for diagnosing internal organs since it is non-invasive. Shadows are often appear in u... [more] | MI2018-96 pp.151-156 |
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| MI | 2019-01-23 14:00 |
Okinawa | [Short Paper]
The blood vessels analysis of 3D lung microstructure using SRmicroCT images Shota Fuketa, Kurumi Saito, Satoru Ohnishi, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Keiji Umetani (JASRI), Hiroaki Sakai (Hyogo AGMC), Yasutaka Nakano (Shiga Univ. of Med. Sci.), Toshihiro Okamoto (Cleveland Clinic), Harumi Itoh (Univ. of Fukui) MI2018-97 |
Changes on CT of images at micro level from the normal lung, which indicate a very early stage lung disease and quantita... [more] | MI2018-97 pp.157-159 |
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| MI | 2019-01-23 14:00 |
Okinawa | [Short Paper]
A Lung Cancer Risk Prediction Model based on Clinical Information and Chest CT Images Analyses Takeru Kageyama, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Masahiko Kusumoto (National Cancer Center), Hironobu Ohmatsu (Abashiri Prison), Yoshiki Aokage, Takaaki Tsuchida, Yuji Matsumoto (National Cancer Center), Kenji Eguchi (Teikyo Univ.), Masahiro Kaneko (Tokyo Health Service Association Health Support Center) MI2018-98 |
Lung cancer accounts for the number of cancer deaths first, and it is on an increasing trend. Although lung cancer CT sc... [more] | MI2018-98 pp.161-163 |
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