Development of methods for structure analysis based on generative learning and its application to understanding of medical images
Project/Area Number |
23700220
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Perception information processing/Intelligent robotics
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Research Institution | Aichi Institute of Technology |
Principal Investigator |
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Project Period (FY) |
2011 – 2013
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Project Status |
Completed (Fiscal Year 2013)
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Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2013: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
|
Keywords | パターン認識 / 医用画像処理 / 生成型学習 / 医用画像理解 |
Research Abstract |
In this research project, we developed methods for recognizing organs and diseases in medical images based on the generative learning approach, which is robust to the data with large variance such as human organs. In the recognition of the airway and blood vessel trees, we investigated effective image features for the generative learning and extracted them from medical images accurately. In the recognition of organs, we constructed an ATLAS, which represents variations of organs mathematically, and extracted them accurately. In the lymph nodes detection, we developed a novel filter which responses to the lymph nodes specifically, and detected lymph nodes with high accuracy. We confirmed that the generative learning approach was effective for recognition of human organs and diseases.
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Report
(4 results)
Research Products
(33 results)
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[Presentation] Radial Structure Tensorおよび機械学習に基づく縦隔リンパ節検出手法2013
Author(s)
小田 紘久, 羅 雄彪, 二村 幸孝, 小田 昌宏, 北坂 孝幸, 岩野 信吾, 本間 裕敏, 高畠 博嗣, 森 雅樹, 名取 博, 森 健策
Organizer
電子情報通信学会技術研究報告, MI2013-55
Place of Presentation
広島市立大学
Related Report
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[Presentation] CAD System for Mediastinal Lymph Node Diagnosis: Automated Segmentation and Visualization of Mediastinal Lymph Nodes from CT Images
Author(s)
Kensaku Mori, Masahiro Oda, Yukitaka Nimura, Yoshihiko Nakamura, Takayuki Kitasaka, Shingo Iwano, Mitsuhiro Kishimoto, Masaki Mori, Hirotsugu Takabatake, Hirotoshi Homma, Hiroshi Natori
Organizer
RSNA (Radiological Society of North America) Scientific Assembly and Annual Meeting Program 2012
Place of Presentation
Chicago, United States
Related Report
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[Presentation] Multi-organ Segmentation from 3D Abdominal CT Images using Patient-Specic Weighted-probabilistic Atlas
Author(s)
Chengwen Chu, Masahiro Oda, Takayuki Kitasaka, Kazunari Misawa, Michitaka Fujiwara, Yuichiro Hayashi, Robin Wolz, Daniel Rueckert, and Kensaku Mori
Organizer
Proceedings of SPIE, Vol.8669, Medical Imaging 2013: Image Processing
Place of Presentation
Florida, United States
Related Report
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