2007 Fiscal Year Final Research Report Summary
Intelligent CAD based on understanding of local pathological structures
| Project/Area Number |
15070208
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas
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| Allocation Type | Single-year Grants |
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| Review Section |
Science and Engineering
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| Research Institution | Yamaguchi University |
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Principal Investigator |
KIDO Shoji Yamaguchi University, Graduate School of Medicine, Professor (90314814)
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| Co-Investigator(Kenkyū-buntansha) |
SHOUNO Hayaru Yamaguchi University, Graduate School of Medicine, Associate Professor (50263231)
MATSUMOTO Tsuneo Yamaguchi University, Graduate School of Medicine, Associate Professor (70116755)
MATSUNAGA Naofumi Yamaguchi University, Graduate School of Medicine, Professor (40157334)
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| Project Period (FY) |
2003 – 2006
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| Keywords | MDCT / local pathological status / intellectual CAD / diffuse lung disease / feature analysis / segmentation / platform / plug-in |
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| Research Abstract |
The outline of our research results is summarized to the following four items:
1. Pattern classification of diffuse lung diseases using MDCT volume data
Diffuse lung disease is one of targets for our study. We have developed an algorithm of diffuse lung analysis for whole lungs obtained from MDCT volume data. In our algorithm, whole lungs are diagnosed as one of seven diffuse lung disease patterns.
2. Function Analysis of Pulmonary Respiration
COPD is one of targets for function analysis of pulmonary respiration. For the diagnosis of COPD, we have developed a radial measurement of bronchus. And also, for the evaluation of emphysema, we have developed an algorithm of lobar segmentation. Moreover, we have developed a measurement algorithm of displacements for ribs and diaphragms by use of inspiratory and expiratioy MDDCT images.
3. Development of a CAD platform
We have developed a CAD platform named "MARIMO" for supporting image diagnoses of radiologists for multi-organ and multi-diseases.
4. Analysis of Auscultation Sounds
For evaluation of diffuse lung diseases, such as pneumonia and COPD, we have developed an algorithm of auscultation sounds. We have achieved more than 90% recognition rate for differentiation of auscultation sounds. And also, we compared the auscultation sound with MDCT images.
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Research Products
(76 results)
