首页> 外文会议>IEEE-EMBS Conference on Biomedical Engineering and Sciences >Detection of Aortic Valve Using Deep Learning Approaches
【24h】

Detection of Aortic Valve Using Deep Learning Approaches

机译:使用深度学习方法检测主动脉瓣

获取原文

摘要

Detection of the aortic valve is one of the critical processes in the diagnosis of cardiovascular diseases. Automatic detection of the aortic valve can assist in improving the diagnostic precision and can further be used for different medical studies like image registration and segmentation. The manual detection of the aortic valve is time-consuming and labor-intensive. The machine learning method is utilized for the automatic detection of the aortic valve in this preliminary study. AlexNet convolutional neural network architecture is used due to its high accuracy for the desired purpose. The trained model was tested on a patient dataset of 120 andthe method was found to be able to detectthe aortic valve 95% accurately.
机译:主动脉瓣的检测是心血管疾病诊断中的关键过程之一。 主动脉瓣的自动检测可以有助于提高诊断精度,并且可以进一步用于图像配准和分割等不同的医学研究。 主动脉瓣的手动检测是耗时和劳动密集型的。 该机器学习方法用于在该初步研究中自动检测主动脉瓣。 由于其高精度,因此使用了AlexNet卷积神经网络架构以获得所需目的。 培训的模型在120的患者数据集上进行测试,并且发现该方法能够精确地检测主动脉瓣95%。

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