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Medical image computing plays an increasingly important role in the field of biomedical research and clinical applications. Research Centre for Medical Image Computing (RC-MIC) focuses on the development of novel techniques for medical image computing and the promotion of the application of computational methods in clinical diagnosis and research.

  

Medical imaging is a powerful tool for investigating into normal and pathological conditions of human body. The role of medical imaging in medical diagnosis and treatment is expanding with the increasing demand of finding ways to visualize the internal organ structure and metabolism. Image computing techniques, such as image reconstruction, post-processing, segmentation, and registration, are among the key components embedded in large-scale image acquisition systems and clinical devices.

 

The application of medical image computing in neurological diseases is one of our main research fields. Neuro imaging is an important non-invasive tool for the examination and diagnosis of patients with neurological diseases, for example, the location and scope of the infarct region can be examined easily by experienced clinicians on the radiological images, so that clinical diagnosis can be supported by evidence. The advances in the field of computational neuro imaging provide the feasibility to derive quantitative information from neuro images such as CT, MRI and PET. We have done some and will do more in the future to develop specific computational tools for quantitative neuro imaging studies to assist clinical research.

 

Computing of orthopedic images is another main scope of our research. Detecting imaging abnormality to characterize and uncover the pathogenesis of Adolescent Idiopathic Scoliosis is one of our major research interests.  Through the years, we have been analyzing the brain MRI, vestibular system, peripheral bone shape, spine, and skull to provide quantitatively evidence to understand this disease.

Prof. Wang Defeng

Address:

Department of Imaging and Interventional Radiology,

The Chinese University of Hong Kong, Shatin, NT

Phone:

852-2632-2975

Email:

dfwang@cuhk.edu.hk