• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Digital Imaging >BRISC—An Open Source Pulmonary Nodule Image Retrieval Framework
【24h】

BRISC—An Open Source Pulmonary Nodule Image Retrieval Framework

机译：BRISC-开源肺结节图像检索框架

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We have created a content-based image retrieval framework for computed tomography images of pulmonary nodules. When presented with a nodule image, the system retrieves images of similar nodules from a collection prepared by the Lung Image Database Consortium (LIDC). The system (1) extracts images of individual nodules from the LIDC collection based on LIDC expert annotations, (2) stores the extracted data in a flat XML database, (3) calculates a set of quantitative descriptors for each nodule that provide a high-level characterization of its texture, and (4) uses various measures to determine the similarity of two nodules and perform queries on a selected query nodule. Using our framework, we compared three feature extraction methods: Haralick co-occurrence, Gabor filters, and Markov random fields. Gabor and Markov descriptors perform better at retrieving similar nodules than do Haralick co-occurrence techniques, with best retrieval precisions in excess of 88%. Because the software we have developed and the reference images are both open source and publicly available they may be incorporated into both commercial and academic imaging workstations and extended by others in their research.
机译：我们为肺结节的计算机断层扫描图像创建了基于内容的图像检索框架。当出现结核图像时，系统会从肺图像数据库联盟（LIDC）准备的集合中检索相似结核的图像。系统（1）根据LIDC专家注释从LIDC集合中提取单个结核的图像，（2）将提取的数据存储在平面XML数据库中，（3）为每个结节计算一组定量描述符，这些描述符提供了较高的（4）使用各种措施来确定两个结节的相似性，并对选定的查询结节执行查询。使用我们的框架，我们比较了三种特征提取方法：Haralick共现，Gabor滤波器和Markov随机字段。与Haralick共现技术相比，Gabor和Markov描述符在检索相似结节方面表现更好，其最佳检索精度超过88％。由于我们开发的软件和参考图像都是开源的，并且可以公开获得，因此它们可以合并到商业和学术成像工作站中，并可以由其他人对其进行扩展。

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