Multi-level medical image semantic modeling approach based on statistical learning

作者：Lin, Chun-Yi^*; Yin, Jun-Xun; Gao, Xue; Chen, Jian-Yu; Sun, Shao-Hui

来源：Journal of Shenzhen University Science and Engineering, 2007, 24(2): 138-143.

• Hierarchical Bayesian network
• Machine learning
• Medical image
• Semantic modeling

A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in a small set of samples. SVMs (support vector machines) was used to map low-level image features into object semantics, then high-level semantics was captured through fusing these object semantics using a Bayesian network. A multi-layer medical image semantic model was built to aim to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. To validate the method, a multilevel semantic model was built from a small set of astrocytona MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytona in malignant degree. Experiment results show that this approach is effective to enable multi-level interpretation of astrocytona MRI. It out performs the Bayesian network-based models using k-nearest neighbor classifiers (K-NN) or Gaussion mixture models (GMM).

• 出版日期2007-4
• 单位华南理工大学; 中山大学