| 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 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Aichi Institute of Technology |
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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)
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| Keywords | パターン認識 / 医用画像処理 / 生成型学習 / 医用画像理解 |
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| 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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