Image analysis of placental issues using three-dimensional ultrasound and color power Doppler based on Support Vector Machine

Qi Wang; Diyun Xu; Jianguo Liu

doi:10.1117/12.832404

30 October 2009 Image analysis of placental issues using three-dimensional ultrasound and color power Doppler based on Support Vector Machine

Qi Wang, Diyun Xu, Jianguo Liu

Author Affiliations +

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74971T (2009) https://doi.org/10.1117/12.832404
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

With the development of medical science, three-dimensional ultrasound and color power Doppler tomography shooting placenta is widely used. To determine whether the fetus's development is abnormal or not is mainly through the analysis of the capillary's distribution of the obtained images which are shot by the Doppler scanner. In this classification process, we will adopt Support Vector Machine classifier. SVM achieves substantial improvements over the statistical learning methods and behaves robustly over a variety of different learning tasks. Furthermore, it is fully automatic, eliminating the need for manual parameter tuning and can solve the small sample problem wonderfully well. So SVM classifier is valid and reliable in the identification of placentas and is more accurate with the lower error rate.

Citation Download Citation

Qi Wang, Diyun Xu, and Jianguo Liu "Image analysis of placental issues using three-dimensional ultrasound and color power Doppler based on Support Vector Machine", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74971T (30 October 2009); https://doi.org/10.1117/12.832404

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