• 主题
高级搜索  >
历史搜索 清空历史
首页> 美国政府科技报告 >Prior Pertinence Evaluation Using Fuzzy Set and Bayes Theory For Esophagus Wall Segmentation.
【24h】

Prior Pertinence Evaluation Using Fuzzy Set and Bayes Theory For Esophagus Wall Segmentation.

机译：模糊集和贝叶斯理论在食管壁分割中的先验相关性评价。

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In this work, our interest is related to the esophagus inner and outer wall segmentation from ultrasound images sequences. We aim to elaborate a general methodology of data mining that coherently links works on data selection and fusion architectures, in order to extract useful information from raw data. In the presented method, based on fuzzy logic, some fuzzy propositions are defined using physicians a priori knowledge. The use of probability distributions, estimated thanks to a learning base, allows the veracity of these propositions to be qualified. This promising idea enables information to be managed through the consideration of both information imprecision and uncertainty. By considering that, the fuzzyfication process is optimized relatively to a given criteria using a genetic algorithm. We conclude this paper with some preliminary results and outline some further works.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号