首页> 外文会议>International Machine Vision and Image Processing Conference >AUTOMATIC LUNG NODULE DETECTION FROM CHEST CT DATA USING GEOMETRICAL FEATURES: INITIAL RESULTS
【24h】

AUTOMATIC LUNG NODULE DETECTION FROM CHEST CT DATA USING GEOMETRICAL FEATURES: INITIAL RESULTS

机译:使用几何特征从胸部CT数据检测自动肺结核:初始结果

获取原文

摘要

In this paper, a complete system for automatic lung nodule detection from Chest CT data is proposed. The proposed system includes the methods of lung segmentation and nodule detection from CT data. The algorithm for lung segmentation consists of surrounding air voxel removal, body fat/tissue identification, trachea detection, and pulmonary vessels segmentation. The nodule detection algorithm comprises of candidate surface generation, geometrical feature generation and classification. The proposed system shows 88.2percent sensitivity for nodule >=3 mm with 8.91 false positive per dataset.
机译:本文提出了一种从胸部CT数据的自动肺结核检测完整系统。所提出的系统包括来自CT数据的肺分段和结节检测方法。肺分割算法包括周围的空气体素去除,体脂/组织鉴定,气管检测和肺血管分割。结节检测算法包括候选表面生成,几何特征生成和分类。所提出的系统显示出88.2个结节的灵敏度> = 3 mm,每个数据集有8.91个假阳性。

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