Currently the voxel based registration methods have been used widely such as the well known mutual information (MI). Although the accuracy of their results is plausible, the registration procedure is slow. This paper ...Currently the voxel based registration methods have been used widely such as the well known mutual information (MI). Although the accuracy of their results is plausible, the registration procedure is slow. This paper proposed some methods to rigid registration based on mutual information, aiming for an acceleration of the registration process without significantly loss of precision in the final results. The efficiency of these methods is examined by registration of CT MR and PET MR. Experimental results show that the speedup is effective and efficient. By using the fast methods, the registration of 3 D medical image could also be implemented on PC rapidly.展开更多
为了适应“新医科+新工科”背景下创新型卓越生物医学工程人才培养需求,提高医学图像处理课程教学质量。笔者团队对医学图像处理课程进行了课程设计改革并实践。基于UbD(Understanding by Design)理论,突出医学应用,将医学图像处理技术...为了适应“新医科+新工科”背景下创新型卓越生物医学工程人才培养需求,提高医学图像处理课程教学质量。笔者团队对医学图像处理课程进行了课程设计改革并实践。基于UbD(Understanding by Design)理论,突出医学应用,将医学图像处理技术与人工智能、大数据、5G通信等先进技术交叉融合,对医学图像处理课程进行教学设计,并在我校生物医学工程专业第6学期进行了教学实践。本课程设计以理解为教学目的,课程目标明确,课程内容满足“新工科+新医科”要求,考核方式能够评估学生对教学内容的理解程度。实践证明学生对教学整体满意度较高。展开更多
文摘Currently the voxel based registration methods have been used widely such as the well known mutual information (MI). Although the accuracy of their results is plausible, the registration procedure is slow. This paper proposed some methods to rigid registration based on mutual information, aiming for an acceleration of the registration process without significantly loss of precision in the final results. The efficiency of these methods is examined by registration of CT MR and PET MR. Experimental results show that the speedup is effective and efficient. By using the fast methods, the registration of 3 D medical image could also be implemented on PC rapidly.
文摘为了适应“新医科+新工科”背景下创新型卓越生物医学工程人才培养需求,提高医学图像处理课程教学质量。笔者团队对医学图像处理课程进行了课程设计改革并实践。基于UbD(Understanding by Design)理论,突出医学应用,将医学图像处理技术与人工智能、大数据、5G通信等先进技术交叉融合,对医学图像处理课程进行教学设计,并在我校生物医学工程专业第6学期进行了教学实践。本课程设计以理解为教学目的,课程目标明确,课程内容满足“新工科+新医科”要求,考核方式能够评估学生对教学内容的理解程度。实践证明学生对教学整体满意度较高。
