| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
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| Outline of Final Research Achievements |
In this work, we collected a large number of three-dimensional CT images. The anatomical structures and local image appearances in those images were arranged. We developed a machine-learning based approach to recognize and extract anatomical structures automatically from the CT images, and integrated that information into the database. We applied the database to predicting the risk of breast cancers and vertebral fractures in preventive medicine, and 3D printing of the patient specific models for uterus surgical planning.The aim of this work of “Upgrading of the CT image database by automatically attaching the meta-information” was almost realized.
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