A Feasibility Study on the Improvement of CT Image with the Back Propagation Neural Network

摘要：

　　It had been a major concern about multi-slice X-ray CT for its high radiation dose delivered to a patient.In order to reduce the radiation dose,one can either limit the dose per projection,or reduce the number of projections,or both.However,it was shown that artifact will appear when limited projections were used.In this study,the feasibility of using back propagation type artificial neural network to improve the image reconstructed using the filtered back projection is studied.Two networks were trained to reconstructed image by input information calculated using the filtered back projection method from 32,and 64 projections respectively.A series tests are also conducted to evaluate the performance of the trained networks.The results show that if information of 32 or 64 projections was used,the reconstructed images are generally improved by the use of the trained network.

关键词： X-ray computer tomography artificial neural network

作者: Shih-Chieh Lin Tse-Li Wang

作者单位: Dept. of Power Mechanical Engineering, National Tsing Hua University, Hsin-Chu, Taiwan 300

会议类型: 国际会议

会议名称: 2012第八届精密工程测量和仪器仪表国际研讨会(ISPEMI2012)

会议地点: 成都

会议语种:英文

页码: 1-7

在线出版日期: 2012-08-08（万方平台首次上网日期，不代表论文的发表时间）