摘要： 给出一种基于统计变形模型的生物医学数据恢复算法。该算法统计模型分为已知和未知两部分，利用统计模型构成的先验信息和待恢复数据的已知部分估算数据的未知部分。肝脏边缘缺失数据恢复实验结果表明，只要待恢复点控制在40%以下，并采用适当的分辨率，就可以将恢复误差控制在1%以内。

关键词: 统计变形模型, 主动形状模型, 数据恢复

Abstract: A biomedical data restoration algorithm based on statistical deformable model is proposed. Specifically, the statistical model is partitioned into known and unknown parts, and the unknown data are estimated by the prior knowledge constructed by the statistical model and the known data. Experiments on missing liver edge points demonstrate that the restoration error can be controlled at less than 1% under 40% unknown data points with proper resolution.

Key words: statistical deformable model, active shape model, data restoration

中图分类号: 

• TP391.41