| Project/Area Number |
05650416
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | Keio University |
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Principal Investigator |
NAKAJIMA Masato Dept.of Elec., Eng., Keio University Professor, 理工学部, 教授 (20051766)
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| Co-Investigator(Kenkyū-buntansha) |
OMOTO Ryozo Saitama Medical Univ.Professor, 医学部, 教授 (80112647)
NATORI Mitiya Sch.of Med., Keio Univ.Lecturer, 医学部, 専任講師 (80101913)
SAITO Hideo Dept.of Elec., Eng.Research Associate, 理工学部, 助手 (90245605)
NAKAZAWA Kazuo Dept.of Mechanical Eng.Lecturer, 理工学部, 専任講師 (80217695)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1994: ¥900,000 (Direct Cost: ¥900,000)
Fiscal Year 1993: ¥1,200,000 (Direct Cost: ¥1,200,000)
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| Keywords | Ultrasound image / M-mode image / Boundary extraction / Fuzzy reasoning / 4D image / Relaxation techniques / Heart / Depth cueing technique / 超音波エコー画像 / 3次元表示 / ニューラル・ネットワーク / ランバート・ツェーディング / 局所的ヒストグラム均等化法 |
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| Research Abstract |
The purpose of this study is to develop a new method for displaying 3D motion image of target organ from ultrasound images. To display 3D image finely, it is essential to extract the organ boundaries exactly. But it is difficult to detect the organ boundaries from ultrasound images exactly and automatically. Therefore, we developed the boundary extraction method using fuzzy reasoning and relaxation techniques. As a result of applying the experiment to fetal clinical data, we obtained the high quality 3D image of fetus. And besides, we applyed this algorithm to cardiac clinical data. In the case of cardiac clinical data, the quality of B-mode image is worse, and so it is much difficult to detect the organ boundaries. B-mode image is ultrasound echo image. By the way, M-mode image is used widely in cardiac diagnosis. Because it is much ease to recognize the boundary. Then we applyed this improved method to clinical data. 4D data were acquired by following two ways. First we acquired 4-D data at an intervals of 2.5 degrees with ECG.Other we acquired 4-D data with transesophageal scan every a heartbeat. We applyed the improved method to the clinical data, and extracted organ boundaries, and displayd 4D image using depth cueing technique. It was found that significant 4D image obtained by applying the algorithm.
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