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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2024-03-03 10:40 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Pilot study of multitask learning for upper abdominal organ extraction and lesion detection on PET/CT images Kohei Yoshida, Mitsutaka Nemoto, Kazuki Otani (Kindai Univ.), Hayato Kaida (KU Hosp), Yuichi Kimura, Takashi Nagaoka, Katsuhiro Mikami (Kindai Univ.), Takahiro Yamada, Kohei Hanaoka (KU Hosp), Tatsuya Tsuchitani, Kazuhiro Kitajima (HMU Hosp), Kazunari Ishii (KU Hosp)  MI2023-37 |
As one of the studies for highly accurate detection of adrenal metastatic lesions on FDG-PET/CT images, multi-task learn... [more] | MI2023-37 pp.25-27 |
| MI | 2024-03-03 11:40 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Weak supervised chest lesion detection on FDG-PET/CT Images using Pix2Pix image modality translation Kazuki Otani, Kohei Yoshida, Mitsutaka Nemoto (Kindai Univ.), Hayato Kaida (KU Hosp), Yuichi Kimura, Takashi Nagaoka, Katsuhiro Mikami (Kindai Univ.), Takahiro Yamada, Kohei Hanaoka (KU Hosp), Tsuchitani Tatsuya, Kazuhiro Kitajima (HMU Hosp), Kazunari Ishii (KU Hosp) MI2023-42 |
In this study, we propose a method for detecting thoracic lesions on PET/CT images using 3D Pix2Pix, which learns a tran... [more] | MI2023-42 pp.36-38 |
| MI | 2024-03-04 13:28 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Experimental validation of relationship between training data amount and accuracy of automatic annotation in developing image diagnosis AI Koki Muranaka, Mitsutaka Nemoto, Yuichi Kimura, Takashi Nagaoka, Katsuhiro Mikami, Yukako Nakamae (Kindai Univ.), Takeharu Yoshikawa (Tokyo Univ.) MI2023-77 |
To reduce the development cost of image diagnosis AI systems, we have studied and proposed an automatic process for crea... [more] | MI2023-77 pp.149-151 |
| MI | 2023-03-06 14:55 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
MI2022-87 |
(To be available after the conference date) [more] | MI2022-87 pp.75-77 |
| MI | 2021-03-16 16:30 |
Online | Online | [Short Paper]
Yuto Kanazawa, Takashi Nagaoka, Yuichi Kimura, Mitsutaka Nemoto (Kindai Univ) MI2020-82 |
(To be available after the conference date) [more] | MI2020-82 pp.150-151 |
| MICT, MI | 2020-11-04 16:10 |
Online | Online | Performance of automated melanoma diagnosis by adding lesion information to deep convolutional neural network Ginji Hirano, Mitsutaka Nemoto, Yuich Kimura, Takashi Nagaoka (Kindai University) MICT2020-20 MI2020-46 |
Melanoma is a type of superficial tumor, which is highly malignant. Early-stage melanoma is difficult to diagnose becaus... [more] | MICT2020-20 MI2020-46 pp.62-64 |
| MI | 2020-01-29 09:55 |
Okinawa | OKINAWAKEN SEINENKAIKAN | Automated dection for neck and thoracic lesions on FDG-PET/CT by lesion enhancement using one-class SVM Atsuko Tanaka, Mitsutaka Memoto, Hayato Kaida, Yuichi Kimura, Takashi Nagaoka, Takahiro Yamada, Kazuyuki Ushifusa (Kindai Uni), Kohei Hanaoka (Kindai Uni Hosp), Kazuhiro Kitajima (Hyogo Col of Med), Tatsuya Tsuchitani (Hosp of Hyogo Col of Med), Kazunari Ishii (Kindai Uni) MI2019-67 |
We propose an anomaly detection based method to detect primary and metastatic lesions in the cervical and thoracic regio... [more] | MI2019-67 pp.11-14 |
| MI | 2020-01-29 10:05 |
Okinawa | OKINAWAKEN SEINENKAIKAN | A study of generalized generation of image features for computer-aided detection systems based on unsupervised learning with normal datasets
-- Experimental evaluations of feature generation by small datasets -- Kazuyuki Ushifusa, Mitsutaka Nemoto(, Yuichi Kimura, Takashi Nagaoka, Takahiro Yamada, Atsuko Tanaka (Kindai Uni.), Naoto Hayashi (The Uni of Tokyo Hosp) MI2019-68 |
In a computer-aided detection system, image features are essential factors. In this study, we propose an image feature g... [more] | MI2019-68 pp.15-18 |
| SIP, EA, SP, MI (Joint) [detail] |
2018-03-19 13:40 |
Okinawa | A pilot study to detect anatomical landmarks using convolutional neural network Mitsutaka Nemoto, Shogo Watanabe, Yuichi Kimura (Kindai Univ.), Shouhei Hanaoka, Yukihiro Nomura, Takeharu Yoshikawa, Naoto Hayashi (Univ. of Tokyo) MI2017-80 |
[more] | MI2017-80 pp.47-50 |
|
| MI | 2015-03-03 16:36 |
Okinawa | Hotel Miyahira | An interim report on UTH CAD Challenge 2014
-- Preliminary study for training and temporal evaluation of CAD software in clinical environment -- Yukihiro Nomura (Univ. of Tokyo), Yoshitaka Masutani (Hiroshima City Univ.), Shunsuke Kudo, Takahiro Uehara, Ryoji Hirano, Toshiya Nakaguchi (Chiba Univ.), Shouhei Hanaoka, Mitsutaka Nemoto, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Univ. of Tokyo) MI2014-117 |
Computer-assisted detection/diagnosis (CAD) software has been developed by many research groups, and commercial CAD soft... [more] | MI2014-117 pp.317-320 |
| MI | 2013-09-13 09:50 |
Chiba | Pilot study of anatomical landmark detection adapted to change of body posture Mitsutaka Nemoto, Yoshitaka Masutani, Shouhei Hanaoka, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Univ. of Tokyo) MI2013-37 |
[more] | MI2013-37 pp.5-10 |
|
| MI | 2013-07-18 10:35 |
Miyagi | Comparison of sparse non-directional graphical models on anatomical landmark distances by the Smoothly Clipped Absolute Deviation (SCAD) and the Graphical Lasso Shouhei Hanaoka (Univ. of Tokyo Hospital), Yoshitaka Masutani (Univ. of Tokyo Hospital/Univ. of Tokyo), Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi (Univ. of Tokyo Hospital), Kuni Ohtomo (Univ. of Tokyo Hospital/Univ. of Tokyo) MI2013-20 |
We have been developed an automatic detection system for anatomical landmarks in CT images. The system utilizes a multi... [more] | MI2013-20 pp.7-12 |
|
| MI | 2013-07-18 11:05 |
Miyagi | On Uncertainty of Anatomical Landmarks and Their Detectability by using Appearance Models Yoshitaka Masutani, Mitsutaka Nemoto, Shouhei Hanaoka, Naoto Hayashi, Kuni Ohtomo (Univ. of Tokyo Hosipital) MI2013-21 |
The anatomical landmarks are defined at local structures with salient features such as projections on bones or bifurcati... [more] | MI2013-21 pp.13-16 |
|
| MI | 2013-01-24 10:30 |
Okinawa | Bunka Tenbusu Kan | Construction of a sparse non-directional graphical model on anatomical landmark distances by the Graphical Lasso
-- Feasibility study for application to automatic landmark detection system -- Shouhei Hanaoka, Yoshitaka Masutani, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Univ. of Tokyo) MI2012-64 |
We have been developed an automatic detection system for anatomical landmarks in CT images. The system utilizes a non-s... [more] | MI2012-64 pp.13-18 |
| MI | 2013-01-25 13:10 |
Okinawa | Bunka Tenbusu Kan | A pilot study of lung voxel classification for auto-detecting ground glass opacity nodules in chest CT images Mitsutaka Nemoto, Yoshitaka Masutani, Shouhei Hanaoka, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Univ. Tokyo) MI2012-109 |
In this study, we examine various voxel classification methods for auto-extracting ground glass opacity (GGO) nodule can... [more] | MI2012-109 pp.245-248 |
| MI | 2013-01-25 15:15 |
Okinawa | Bunka Tenbusu Kan | Construction of probability model for radiologists' detection failures in a routine reading environment Yukihiro Nomura, Yoshitaka Masutani, Mitsutaka Nemoto, Shouhei Hanaoka, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (The Univ. of Tokyo) MI2012-121 |
In order to realize CAD display interfaces based on radiologists' reading characteristics, it is important to construct ... [more] | MI2012-121 pp.305-310 |
| MI | 2012-09-04 10:15 |
Tokyo | Univ. of Tokyo | Automatic detection method for anatomical landmarks on the soft tissue in enhanced abdominal CT volumes Shouhei Hanaoka, Yoshitaka Masutani, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Tokyo Univ.) MI2012-40 |
We have been developed an automatic detection system for anatomical landmarks in plain torso CT images. However, the sy... [more] | MI2012-40 pp.7-12 |
| MI | 2012-07-20 11:00 |
Yamagata | Yamagata Univ. | Preliminary study for undersampling non-lesion voxel in training of voxel-based classification for lesion detection Yukihiro Nomura, Mitsutaka Nemoto, Yoshitaka Masutani, Shouhei Hanaoka, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (The Univ. of Tokyo) MI2012-32 |
In voxel-based classification for lesion detection, training of a classifier is time-consuming since the number of train... [more] | MI2012-32 pp.59-64 |
| MI | 2012-01-19 11:00 |
Okinawa | Web-based CAD server for clinical use, evaluation, and incremental learning
-- Incremental learning of CAD software based on multicenter trial in teleradiology environment -- Yukihiro Nomura, Yoshitaka Masutani, Naoto Hayashi, Soichiro Miki, Mitsutaka Nemoto, Shouhei Hanaoka, Takeharu Yoshikawa, Kuni Ohtomo (The Univ. of Tokyo) MI2011-81 |
We have been building a web-based CAD server (CIRCUS CS) that enables radiologists to use CAD software and to give feedb... [more] | MI2011-81 pp.23-28 |
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| MI | 2012-01-19 17:00 |
Okinawa | Accuracy improvement of the landmark detection system withafastout-of-imaging-range LM position estimation algorithm Shouhei Hanaoka, Yoshitaka Masutani, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo (Univ. of Tokyo) MI2011-115 |
We have been developed an automatic detection system for anatomical landmarks in torso CT images. However, the system h... [more] | MI2011-115 pp.209-214 |
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