New image recognition from 3D laparoscopic image by artificial intelligence
Project/Area Number |
15K01330
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Medical systems
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Research Institution | Kobe University |
Principal Investigator |
Kanaji Shingo 神戸大学, 医学部附属病院, 助教 (10637052)
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Co-Investigator(Kenkyū-buntansha) |
角 泰雄 神戸大学, 医学研究科, 特命教授 (00529521)
中村 哲 神戸大学, 医学部附属病院, 講師 (10403247)
掛地 吉弘 神戸大学, 医学研究科, 教授 (80284488)
大竹 義人 奈良先端科学技術大学院大学, 先端科学技術研究科, 准教授 (80349563)
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Co-Investigator(Renkei-kenkyūsha) |
SATOU Yoshinobu 奈良先端科学技術大学院大学, 情報科学研究科, 教授 (70243219)
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Research Collaborator |
Asutin Reiter Johns Hopkins University, Department of Computer Science, Assistant Research Professor
NISHI Masayasu 神戸大学, 医学研究科, 医員
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Project Period (FY) |
2015-04-01 – 2018-03-31
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Project Status |
Completed (Fiscal Year 2017)
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Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2015: ¥2,990,000 (Direct Cost: ¥2,300,000、Indirect Cost: ¥690,000)
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Keywords | コンピュータ外科学 / 3D内視鏡 / 腹腔鏡トレーニング / 画像認識による3次元動作追跡法 / 反射用マーカーによる3次元動作追跡法 / 画像認識による3次元動作の追跡法 |
Outline of Final Research Achievements |
We have reported that 3D can shorten the movement of laparoscopic forceps compared with 2D in training box (Nishi M, Kanaji S et al, Surgery.2016). Further, we have developed the new method of the laparoscopic image recognition from RGB image and depth image with 3D by artificial intelligence. Our method can detect the location of forceps tip automatically only from operative image and track the motion of surgeon.
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Report
(4 results)
Research Products
(23 results)
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[Journal Article] The learning effect of using stereoscopic vision in the early phase of laparoscopic surgical training for novices2018
Author(s)
Harada H, Kanaji S, Nishi M, Otake Y, Hasegawa H, Yamamoto M, Matsuda Y, Yamashita K, Matsuda T, Oshikiri T, Sumi Y
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Journal Title
Surgical endoscopy.
Volume: 32(2)
Issue: 2
Pages: 582-588
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Quantitative comparison of operative skill using 2-and 3-dimensional monitors during laparoscopic phantom tasks.2017
Author(s)
Nishi M, Kanaji S, Otake Y, Harada H, Yamamoto M, Oshikiri T, Nakamura T, Suzuki S, Suzuki Y, Hiasa Y, Sato Y
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Journal Title
Surgery
Volume: 31
Issue: 5
Pages: 1334-1340
DOI
Related Report
Peer Reviewed / Open Access / Acknowledgement Compliant
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[Journal Article] Comparison of two- and three-dimensional display for performance of laparoscopic total gastrectomy for gastric cancer.2017
Author(s)
Kanaji S, Suzuki S, Harada H, Nishi M, Yamamoto M, Matsuda T, Oshikiri T, Nakamura T, Fujino Y, Tominaga M, Kakeji Y.
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Journal Title
Langenbecks Arch Surg
Volume: -
Issue: 3
Pages: 493-500
DOI
Related Report
Peer Reviewed / Open Access
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[Journal Article] Comparing the short-term outcomes of laparoscopic distal gastrectomy with D1+ and D2 lymph node dissection for gastric cancer.2016
Author(s)
Goto H, Yasuda T, Oshikiri T, Kanaji S, Kawasaki K, Imanishi T, Oyama M, Kakinoki K, Ohara T, Sendo H, Fujino Y, Tominaga M, Kakeji Y.
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Journal Title
Asian J Endosc Surg.
Volume: 9
Issue: 2
Pages: 116-21
DOI
Related Report
Peer Reviewed
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[Presentation] THE EFFECT OF STEREOSCOPIC IMAGES FROM USING A THREE-DIMENSIONAL MONITOR TO LAPAROSCOPIC SURGICAL TRAINING FOR NOVICES 2017
Author(s)
Harada H,Kanaji S, Suzuki S,Hasegawa H, Yamamoto M, Matsuda Y, Yamashita K,Matsuda T,Oshikiri T,Sumi Y,Nakamura T,Kakeji Y.
Organizer
SAGES 2017 Annual Meeting
Place of Presentation
ヒューストン
Year and Date
2017-03-22
Related Report
Int'l Joint Research
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[Presentation] Comparison of operative skill using two -and three-dimensional monitor during laparoscopic phantom tasks by the position tracker2017
Author(s)
Nishi M,Kanaji S,Harada H,Hasegawa H,Yamamoto M,Matsuda Y,Yamashita K,Matsuda T,Oshikiri T,Sumi Y,Nakamura T,Suzuki S,Kakeji Y
Organizer
第25回欧州内視鏡外科会議(EAES)
Related Report
Int'l Joint Research
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[Presentation] Segmentation of Surgical Instruments from RGB-D Endoscopic Images using Convolutional Neural Networks: Preliminary Experiments towards Quantitative Skill Assessment.2016
Author(s)
Hiasa, Y., Suzuki, Y., Reiter, A., Otake, Y., Nishi, M., Harada, H., Koyama, K., Kanaji, S., Kakeji, Y., Sato, Y.
Organizer
生体医用画像研究会第 3 回若手発表会
Place of Presentation
大阪
Year and Date
2016-03-12
Related Report
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