Big Medical Data in Brain Imaging
Speaker: Dr. Ruogu Fang, School of Computing and Information Sciences at FIU
Title: Big Medical Data in Brain Imaging
Big data has made significant impacts in every aspect of our life. Medical and health fields have accumulated huge amount of data (with 500 petabytes in 2012 and 25 exabytes in 2020 expected). However, the explosive growth of digital health data does not mean the same increase of knowledge growth. In this talk, I will present the big picture of the challenges faced by the world and the US healthcare system in the age of big medical data, and opportunities open for research, and our advances on using the big medical data for more accurate and safer medical diagnosis. This talk will focus on the leveraging of Big Medical Data for robust, safe and effective brain imaging. With the ever-increasing amount of medical image and health informatics data (CT, MRI, PET, ultrasound, neuron, behavior risk factor surveys, etc.) in the hospitals and medical centers across the world, exploitation of the large-scale medical data would provide invaluable information for the medical image processing and analysis. The quality of medical image is a great challenge at low radiation dose and short acquisition time. Learning-based medical imaging is an inter-disciplinary field that bridges machine learning, computer vision, health informatics and medical imaging. It offers flexible and effective approaches to exploit the inherent structure of the massive medical image data.