Three-Dimensional Probabilistic Neural Network Using for MR Image Segmentation

摘要：

The three-dimensional probabilistic neural network (PNN) is proposed as the core classifier for segmentation of three-dimensional (3-D) magnetic resonance imaging (MRI). The proposed algorithm takes into account the spatial information between image voxels. It adopts the self-organizing map (SOM) neural network to overly segment the 3D MR image, and yield reference voxels necessary for probabilistic density function. The experimental results demonstrate the effectiveness and robustness of the proposed approach.

关键词： three-dimensional adaptive probabilistic neural network structure tensor MR image segmentation.

作者: Lian Yuanfeng Wu Falin

作者单位: College of Geophysics and Information Engineering,China University of Petroleum,Beijing 102249,China School of Instrumentation Science and Opto-electronic Engineering,Beijing University of Aeronautics

会议类型: 国际会议

会议名称: 2011 10th International Conference on Electronic Measurement & Instruments(第十届电子测量与仪器国际会议 ICEMI2011)

会议地点: 成都

会议语种:英文

页码: 847-851

在线出版日期: 2011-08-16（万方平台首次上网日期，不代表论文的发表时间）