Towards AI-Powered Healthcare: Automated Medical Image Analysis via Deep Learning
|Title:||Towards AI-Powered Healthcare: Automated Medical Image Analysis via Deep Learning|
|Date:||February 13, 2019 (Wednesday)|
|Time:||4:00 pm - 5:00 pm|
|Venue:||Room 121, 1/F, Ho Sin-hang Engineering Building, The Chinese University of Hong Kong, Shatin, N.T.|
|Speaker:|| Dr. Qi DOU
Postdoctoral Research Associate
Department of Computing Imperial College London
In modern healthcare, disease diagnosis, assessment and therapy have been significantly depending on the interpretation of medical images, e.g., CT, MRI, Ultrasound, histology images and endoscopy surgical videos. The exploding amount of biomedical image data collected in nowadays clinical centers offer an unprecedented challenge, as well as enormous opportunities, to develop a new-generation of data analytics techniques for improving patient care and even revolutionizing healthcare industry. In the meanwhile, the momentum in cutting-edge AI systems is towards representation learning and pattern recognition via data-driven approaches. In this talk, I will present a series of deep learning methods towards interdisciplinary researches at artificial intelligence and medical image analysis, for improving lesion detection, anatomical structure segmentation and quantification, cancer diagnosis and therapy. The proposed methods cover a wide range of deep learning topics including design of network architectures, novel learning strategies, multi-task learning, adversarial training, domain adaptation, etc. The challenges, up-to-date progresses and promising future directions of AI-powered healthcare will also be discussed.
Dr. Qi DOU is currently a postdoctoral research associate at the Department of Computing at Imperial College London. Before that, she has received her Ph.D. degree in Computer Science and Engineering at The Chinese University of Hong Kong in July 2018, and was a postdoctoral research fellow in the same lab for three months. She got her Bachelor's degree in Biomedical Engineering at Beihang University in China with honor in 2014. Her research interests are in the development of advanced machine learning methods for medical image analysis, with expertise in deep learning. She has won the Best Paper Award of Medical Image Analysis-MICCAI in 2017, the Best Paper Award of Medical Imaging and Augmented Reality in 2016, and MICCAI Young Scientist Award Runner-up in 2016. She has also won the CUHK Postgraduate Research Output Award 2017 and Best Paper Award of CUHK International Doctoral Forum 2016. She was also the winner of Young Scientist Award at the Hong Kong Institution of Science in 2018. She has published 30+ papers in top conferences and journals on the topic of deep learning for medical data analysis. She serves as Area Chair of MIDL’19, PC of IJCAI’19, AAAI’19, IJCAI’18, Reviewer of journals such as IEEE-TMI, IEEE-TBME, IEEE-CYB, Medical Image Analysis, Pattern Recognition, Neurocomputing. Her current Google Scholar citation has reached 1300+ with h-index 17.
Enquiries: Ms. Crystal Tam at tel. 3943 8439
For more information, please refer to http://www.cse.cuhk.edu.hk/en/events
**** ALL ARE WELCOME ****