TAMURA Shinichi Osaka Univ., Graduate School of Medicine, Professor (30029540)
NIKI Noboru The Univ. of Tokushima, Institute of Technology and Science, Graduate school, Professor (80116847)
SUENAGA Yasuhito Nagoya Univ., Graduate School of Information Science, Professor (60293643)
FUJITA Hiroshi Gifu Univ., Graduate School of Medicine, Professor (10124033)
SUGIMOTO Naozo Kyoto Univ., Graduate School of Information, Professor (20196752)
木戸 尚治 山口大学, 大学院・医学系研究科, 教授 (90314814)
|Budget Amount *help
¥36,900,000 (Direct Cost : ¥36,900,000)
Fiscal Year 2007 : ¥2,900,000 (Direct Cost : ¥2,900,000)
Fiscal Year 2006 : ¥8,500,000 (Direct Cost : ¥8,500,000)
Fiscal Year 2005 : ¥8,500,000 (Direct Cost : ¥8,500,000)
Fiscal Year 2004 : ¥8,500,000 (Direct Cost : ¥8,500,000)
Fiscal Year 2003 : ¥8,500,000 (Direct Cost : ¥8,500,000)
The objective of this research project is to develop a multi-organ, multi-disease CAD system that incorporates anatomical knowledge of the human body and diagnostic knowledge of various types of diseases.
Digital atlases of human anatomy (DAHA) have been developed. Based on them various methods of segmentation of organs in the chest and/or abdominal 3D CT images have been developed. They include the bronchus, the blood vessels in the lung area, the diaphragm, the heart, the coronary artery, the stomach wall, the liver, the spleen, the left and right kidneys, the gallbladder, the pancreas, the colon, the portal vein (PV) between the spleen and liver, the esophagus, the abdominal aorta, and the inferior vena cava (IVC).
The characteristics of abnormal regions depend on the type of disease. In order to identify these abnormalities, diagnostic knowledge of various types of diseases is essential. A database of such diagnostic knowledge on the major organs in chest and/or abdominal region, i. e. a digital representation of diagnostic knowledge (DRDK), has been developed.
The DANA and the DRDK are large databases that can be achieved by the collaboration of several research groups. Various types of segmentation methods, organ modeling methods, lesion detection methods, diagnostic methods, etc., must be integrated into one system to develop a multi-organ, multi-disease CAD system. A common platform that can integrate all of those plug-in units has been developed. It is called Pluto. And a prototype of a comprehensive CAD system for multi-organ and multi-disease has been constructed on this platform.
These results suggest that the goal of the research project has been achieved.