| Budget Amount *help |
¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2014: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Outline of Final Research Achievements |
In this project, we developed a new method for constructing statistical shape model of anatomical organs robustly by employing not a normal distribution but a q-exponential distribution for the representation of the variety of the shape in order for estimating appropriate values of parameters even when the number of training data is small. A statistical shape model is constructed from a set of training data and it is not easy to collect the training data as many as the degree of the freedom of the shape variety. When the training data set is small and one employs a normal distribution for the representation, the resultant model overfits to the small training data set and the representation ability is degraded. Each layer of many conventional hierarchical models for the organs is mainly represented by a normal distribution. Using the results of this research, one can automatically select the best representation that maximizes the generalization ability.
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