• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>IEEE Portuguese Meeting in Bioengineering >Automatic Versus Semi-Automatic method for the striatum specific uptake ratio quantification based on 123IFP-CIT SPECT images
【24h】

Automatic Versus Semi-Automatic method for the striatum specific uptake ratio quantification based on 123IFP-CIT SPECT images

机译：基于 123 I FP-CIT SPECT图像的纹状体特异性摄取率定量的自动对半自动方法

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

摘要

The aim of this work was to implement an automatic application (AA) for the quantification of the striatum transaxial slices based on [123I]FP-CIT SPECT (Single Photon Emission Tomography) images. A sample of 68 subjects with and without pathology was collected from the nuclear medicine department of the Hospital Particular de Almada. In order to compare the striatum specific uptake ratios (SUR), a semi-automatic application (SAA) was also developed allowing manual adjustments by a specialist operator. The obtained results were compared with the DaTSCAN® V4 application, from General Electric Healthcare. The experimental results based on SUR demonstrate that the AA can successfully discriminate the healthy patients from the pathological subjects. Additionally, a strong correlation was verified between the AA and the semi-automatic methods (DaTSCAN® V4 and the SAA). These methods also evidence intra and inter-operator variability, suppressed by the AA. The proposed methodology for segmentation and quantification of the striatum transaxial images obtained by [123I]FP-CIT SPECT demonstrated that the developed application can accurately complement the visual analysis, requiring future optimization.
机译：这项工作的目的是基于[ 123 I] FP-CIT SPECT（单光子发射断层扫描）图像。从Almada医院的核医学科收集了68位有或没有病理学的受试者的样本。为了比较纹状体的特定摄取率（SUR），还开发了半自动应用程序（SAA），允许专业操作人员进行手动调整。将获得的结果与DaTSCAN进行比较 ® V4应用程序，来自General Electric Healthcare。基于SUR的实验结果表明，AA可以成功地将健康患者与病理对象区分开。此外，还验证了AA和半自动方法（DaTSCAN）之间的强相关性。 ® V4和SAA）。这些方法还证明了操作者内部和操作者之间的变异性，被AA抑制了。拟议的方法用于分割和量化纹状体横轴图像，通过[ 123 I] FP-CIT SPECT演示了开发的应用程序可以准确地补充视觉分析，需要将来进行优化。

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