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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2023-03-07 17:03 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Automatic extraction of vascular lesions in learning a small number of data using semi-supervised mutual learning Tatsuya Hasunuma (Gifu Univ), Taiki Nozaki, Masaki Matusako (St. Luke's International Hospital), Takeshi Hara, Xiangrong Zhou, Hiroshi Fujita (Gifu Univ)  MI2022-126 |
(To be available after the conference date) [more] | MI2022-126 pp.212-214 |
| MI | 2022-01-27 16:13 |
Online | Online | [Short Paper]
utomatic Extraction of Regions of Vascular Lesions Including Diffuse Lesions in MR Images Using Weakly Supervised Deep Learning Koki Fukaya, Takeshi Hara (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St.Luke's International Hosp.), Tetsuro Katafuchi (Gifu Medical Univ.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2021-87 |
Klippel-Trenaunay-Weber syndrome (KTS) is a type of vascular lesion for which there is no quantitative diagnostic method... [more] | MI2021-87 pp.186-187 |
| MI | 2021-07-08 13:00 |
Online | Online | Automated detection of malignant tumors on PET/CT images using convolutional neural networks and statistical images Takumi Aihara (Gifu Univ.), Masaki Matsusako (St.Luke's International Hospital), Takeshi Hara (Gifu Univ.), Taiki Nozaki (St.Luke's International Hospital), Tetsuro Katafuchi (Gifu University of Medical Science), Satoshi Ito, Masaya Kato (Daiyukai General Hospital), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2021-9 |
In this study, we performed automatic detection of tumors from PET / CT images using Z-score images. The Z-score image i... [more] | MI2021-9 pp.1-6 |
| MI | 2021-03-16 10:45 |
Online | Online | MI2020-69 |
[more] | MI2020-69 pp.92-93 |
| MI | 2021-03-16 13:15 |
Online | Online | [Short Paper]
Feature extraction using AutoEncorder from nodular shadows on chest CT images Yuta Tanaka, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Masaki Matsusako, Taiki Nozaki (St. Luke's Hosp.) MI2020-71 |
Lung cancer mortality in men is 86.7% in 2018. If the benign and malignant lung cancer and the growth rate of nodules ca... [more] | MI2020-71 pp.99-101 |
| MI | 2020-01-29 13:20 |
Okinawa | OKINAWAKEN SEINENKAIKAN | [Short Paper]
Growth process analysis of nodular shadows in chest CT images using function expression Shoko Inagaki, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St. Luke's Hospital) MI2019-79 |
Volume changes of lung nodules were recognized to prognose and to predict the abnormalities in the follow-up treatments.... [more] | MI2019-79 pp.67-69 |
| MI | 2020-01-29 13:20 |
Okinawa | OKINAWAKEN SEINENKAIKAN | [Short Paper]
Automatic segmentation of malignant tumors using PET/CT images and statistical images Manami Haga, Takeshi Hara (Gifu Univ.), Satoshi Ito, Masaya Kato (Daiyukai Hospital), Masaki Matsusako (St.Luke's Hospital), Zhou Xiangrong (Gifu Univ.), Tetsuro Katafuchi (Gifu Univ. of Medical Science), Hiroshi Fujita (Gifu Univ.) MI2019-83 |
The purpose of this study was to develop an automated detection system of tumors in FDG-PET/CT images. In this work, an ... [more] | MI2019-83 pp.77-81 |
| MI | 2020-01-30 10:50 |
Okinawa | OKINAWAKEN SEINENKAIKAN | [Short Paper]
Study of image quality improvement technique using deep learning for nuclear medicine images Masaya Momiuchi, Takeshi Hara (Gifu Univ), Tetsuro Katafuchi (Gifu Univ of Medical Science), Masaki Matsusako (St. Luke's Hospital), Hiroshi Fujita (Gifu Univ) MI2019-102 |
Spatial resolutions in nuclear medical imaging are not equivalent to ordinary medical images such as CT or MR modalities... [more] | MI2019-102 pp.165-168 |
| MI | 2019-07-05 14:00 |
Hokkaido | Future Univ. Hakodate | [Short Paper]
Automated extraction of cartilage regions on knee MR images by deep learning approach Koki Fukaya, Takeshi Hara, Xiangrong Zhou (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St. Luke's HP), Hiroshu Fujita (Gifu Univ.) MI2019-17 |
(To be available after the conference date) [more] | MI2019-17 pp.1-2 |
| MI | 2019-01-22 13:20 |
Okinawa | [Short Paper]
Differences of Segmentation Results by Three Training Data for Cartilage Extraction in Knee MR Images Using Deep Learning Ryoma Aoki, Takeshi Hara (Gifu Univ), Taiki Nozaki, Masaki Matsusako (Dept.of Radiol.,St.Luke's Hosp.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ) MI2018-76 |
Accurate grasp of cartilage area is important for diagnosis and treatment related to arthropathy diseases. In recent yea... [more] | MI2018-76 pp.63-64 |
|
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-20 13:30 |
Okinawa | [Short Paper]
Quantitative image analysis of striatum updake on dopamine transporter imaging based on image registration of brain SPECT/CT and MR images Takeshi Hara, Yuta Takeda, Shogo Yokoi (Gifu Univ.), Masaki Matsusako, Taiki Nozaki (St. Luke's Hosp.), Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2017-100 |
[more] | MI2017-100 pp.123-124 |
|
| MI | 2017-01-18 14:15 |
Okinawa | Tenbusu Naha | [Short Paper]
Nami Nishikwa, Takeshi Hara (Gifu Univ.), Nozaki Taiki, Matsusako Masaki (Dept.of Radiol.,St.Luke's Hosp.), Xiangrong Zhou, Fujita Hiroshi (Gifu Univ.) MI2016-84 |
(To be available after the conference date) [more] | MI2016-84 pp.57-58 |
| MI | 2017-01-18 14:15 |
Okinawa | Tenbusu Naha | [Short Paper]
Syougo Yokoi, Yuta Takeda, Takeshi Hara (Gifu Univ.), Yuki Tanaka (St. Luke's International Hospital), Tetsuro Katafuchi (Gifu Medical Science Univ.), Daisuke Fukuoka (Gifu Univ.), Taiki Nozaki, Masaki Matsusako (St. Luke's International Hospital), Hiroshi Fujita (Gifu Univ.) MI2016-91 |
(To be available after the conference date) [more] | MI2016-91 pp.77-78 |
| MI | 2012-10-29 14:45 |
Yamaguchi | Yamaguchi Univ. | Measurements of depth recognition on stereoscopic scintigrams based on two-altanative forced choice task Takeshi Hara, Katsuaki Yamazaki (Gifu Univ.), Tetsuro Katafuchi (Gifu Med. Univ.), Tatsunori Kobayashi (Junshin Univ.), Masaki Matsusako (St. Luke Hosp.), Chisako Muramatsu, Xiangrong Zhou, Hiroshi Fujita (Gifu Univ.) MI2012-58 |
It is difficult for readers to recognize object depth and overlap in a single scintigraphy. The purpose of this work was... [more] | MI2012-58 pp.55-58 |
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