5月19日，由电子科技大学信息与通信工程学院与格拉斯哥大学共同主办，格拉斯哥学院协办的2021年第3期“电子科技大学-格拉斯哥大学学术论坛”开讲，特别邀请格拉斯哥大学Sandy Cochran教授和信通学院李纯明教授做客本次论坛，分别以“Characteristics of Ultrasound as a Data Source for Medical Imaging”和“MRI Segmentation and Related Issues Based on Knowledge of Imaging and Anatomy”为题带来精彩的学术报告。
本次论坛采用线上形式开展，由格拉斯哥大学副教授赵国栋主持，格拉斯哥学院英方院长Muhammad Ali Imran、格拉斯哥大学Qammer Abbasi博士及相关专业师生100余人通过线上参与论坛。
Sandy Cochran教授首先向我们介绍了基于超声的医学成像原理以及优势，并向大家展示了在临床上提供实时信息等应用，接着，他介绍了超声两项极具发展的应用：在体内的应用（如胶囊内窥镜检查）和在2-D阵列的3-D成像中的应用。他提出在前一种情况下，由于人体中电磁场的衰减，通信信道受到极大的限制;但在后一种情况下，射频数据速率可能会提高一个数量级以上的因数。最后，Sandy Cochran教授指出了超声技术在未来的发展中具有巨大的研究价值。
接下来，李纯明教授结合影像学和解剖学的知识，介绍了医学图像分割的相关问题和解决方案。他从MR图像形成的模型和两个相乘分量的特性分析，提出了一种可扩展局部逼近与积分(SLAI)方法来同时估计偏场和分割脑组织，又从心脏心室的解剖角度出发，介绍一种凸性保留水平集演化模型，从心脏MRI中恢复左心室的心内膜和心外膜，得到与心脏心室解剖相一致的轮廓为凸形的心内膜和心外膜。然后将该方法推广到利用一种新的心室几何结构分割左、右心室。通过实验结果表明其在医学图像分割和偏置场估计方面具有精度和鲁棒性方面的优势。
在最后的交流环节中，Sandy Cochran教授和李纯明教授与参会师生进行了热烈的讨论。
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Sandy Cochran (IEEE Member ’00, Senior Member ’19) received the B.Sc. degree in electronics and computing and the M.B.A. and Ph.D degrees from the University of Strathclyde, Glasgow, U.K. He has held posts in engineering, physics, and medicine at several Scottish universities. He is currently a Professor with the James Watt School of Engineering, University of Glasgow, Glasgow, U.K. He has co-authored approaching 500 journals and conference papers and presentations. His research interests are focused on devices and systems for ultrasound in medicine and life sciences. Topics of particular interest at present are new piezoelectric materials and better utilization of existing materials, microscale and miniature devices for new applications, including microultrasound imaging, ultrasound surgery and ultrasound-targeted drug delivery, and ultrasound systems for intraluminal imaging of the gut. Dr. Cochran is a member of the U.K. Institute of Engineering and Technology, and a Fellow of the U.K. Institute of Physics.
Chunming Li received the B.S. degree in mathematics from Fujian Normal University, Fujian, China, the M.S. degree in mathematics from Fudan University, Shanghai, China, and the Ph.D. degree in electrical engineering from University of Connecticut, Storrs, CT, in 2005. He is currently a full professor in the Department of Information Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu, China. His research interests include the development of innovative algorithms in the fields of image processing, computer vision, and medical imaging. He has published a number of highly cited original articles on image segmentation, level set methods, and related issues in computer vision and medical imaging. He received IEEE Signal Processing Society Best Paper Award in 2013 and 2015 for two of them, both as the first author. He has served as an associate editor or editorial board member for IEEE Trans. Image Processing and Medical Image Analysis. In 2020, he was elevated as an IEEE Fellow for his contributions to computer vision and medical image analysis.
