报告时间：星期二（2016.6.7）9：30pm
报告地点：电子信息楼306
报告人：Örjan Smedby， Ph.D., Professor
邀请人： 陈新建 特聘教授
报告摘要
A quantitative imaging biomarker is an image-based numerical characteristic that can be objectively measured and used as an indicator of a medical condition or pathological process. Such measures are increasingly being used for evaluating the probability, presence, extent or grade of disease, or for evaluating the result of treatment given to the patient. In most cases, the numerical estimates are based on a segmentation of some anatomical structure and related to its volume or shape, or to the mean image intensity in a region.
A few examples of imaging biomarkers will be given. In dementia patients, the volume, thickness or shape of various structures in the brain, such as the hippocampus, can be used for differential diagnosis between different diseases and for assessing the risk of progression. In arterial disease, measures of the reduction of the blood-containing lumen or the thickening of the vessel wall may indicate the degree of atherosclerosis. For evaluating the response of tumours to radiotherapy or drug treatment, volume measurements are essential. The degree of osteoporosis or risk of fracture can be estimated from bone mineral measurements or descriptors of the trabecular bone structure. Accurate, rapid and automated segmentation techniques are needed in most of the applications, and scalar measurements may be supplemented by vector or tensor quantities.
报告人简介：
Örjan Smedby graduated from Medical School at Uppsala University in 1983 and defended his doctoral thesis there in 1992. From 1999 to 2014 he was Professor of Medical Radiology at Linköping University (Faculty of Health Sciences) and since 2004 Professor of Medical image science (Faculty of Engineering, LiU). He was one of the founders of the Center for Medical Image Science and Visualization. Since 2015 he is Professor in Medical Image processing and Visualization at KTH Royal Institute of Technology and director of the Jonasson Centre for Medical Imaging as well as Swedish Bioimaging.