学术报告
Convolutional Neural Network based Metal Artifact Reduction in X-ray Computed Tomography - 张砚博（University of Massachusetts Lowell）
题目：Convolutional Neural Network based Metal Artifact Reduction in X-ray Computed Tomography
报告人: 张砚博（University of Massachusetts Lowell）
Abstract: Patients usually contain various metallic implants (e.g. dental fillings, prostheses), causing severe artifacts in the x-ray CT images. Although a large number of metal artifact reduction (MAR) methods have been proposed in the past decades, the MAR is still one of the major problems in clinical x-ray CT. We developed a convolutional neural network (CNN) based MAR framework, which fuses the information from the original and pre-corrected images to distinguish anatomical structures from artifacts. Experimental results have demonstrated the superior MAR capability of the proposed method to state-of-the-art algorithms.
时间：2017年11月9日（周四）9:30-11:30
地点：首师大校本部新教二楼813教室
欢迎教师和研究生积极参加！
