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医学图像运动伪影校正的实验课程设计

Experimental Course Design of Motion Artifact Correction of Medical Image

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【作者】 张永谦王浩刘可心李诺敏杨威

【Author】 Yongqian Zhang;Hao Wang;Kexin Liu;Nuomin Li;Wei Yang;School of Life Science, Beijing Institute of Technology;School of Medical Technology, Beijing Institute of Technology;Research Institute of Science and Technology, Beijing Institute of Technology;

【通讯作者】 杨威;

【机构】 北京理工大学生命学院北京理工大学医学技术学院北京理工大学科学技术研究院

【摘要】 医学图像处理是生物医学工程本科专业的一门重要课程,它主要利用数学、计算机科学和信息学等工具对医学成像设备产生的医学图像进行处理和加工,已成为医学研究、临床疾病诊断中一个不可或缺的工具和技术手段。但是在实际教学中,如何有效设计医学图像处理实验课程,培养学生发现问题和解决问题的能力,使学生将理论知识应用到临床实践当中面临巨大的挑战。图像退化与复原是医学图像处理中的重要内容,本实验课程围绕医学图像退化及复原中的运动伪影校正这一关键问题,以临床磁共振成像图像为数据来源,进行系统实验课程设计,通过该实验课程的学习,学生不但理解了图像退化及复原原理,掌握医学图像信息处理技能,还提高了设计实验、分析问题解决问题的能力,真正做到理论与临床实践相结合。

【Abstract】 Medical image processing is a key course for undergraduates majoring in biomedical engineering. It mainly utilizes mathematics, computer science and informatics tools to process and analyze the medical images generated by medical imaging equipment. Nowadays, it has become an indispensable method for medical research and clinical diagnosis. However, it is a great challenge to design the experimental course of medical image processing effectively, cultivate undergraduates’ ability to solve problems, and enable undergraduates to apply theoretical knowledge to clinical practice. Image degradation and restoration is an important part of medical image processing. In the present study, we focus on motion artifact correction in medical image degradation and restoration using clinical magnetic resonance imaging as the raw data. Through the study of the experimental course, not only can undergraduates understand the principle of image degradation and restoration, and master the skills of medical image information processing, but they can also improve the ability of designing experiments as well as analyzing and solving problems, so as to truly combine theory with clinical practice.

【基金】 教育部新工科研究与实践项目,突出行业特色的“平行课堂”新工科人才创意创新创业能力培养模式探索与实践(创新创业育人项目群,项目编号:E-CXCYYR20200904);北京理工大学教改项目,数字化新媒体赋能大学生科技创新
  • 【文献出处】 生命科学仪器 ,Life Science Instruments , 编辑部邮箱 ,2022年01期
  • 【分类号】G642.423;R-4
  • 【下载频次】75
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