University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Towards AI-Powered Healthcare: Automated Medical Image Analysis via Deep Learning

Towards AI-Powered Healthcare: Automated Medical Image Analysis via Deep Learning

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Host: Dr Jinming Duan (

Abstract: 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 for medical image analysis and surgical robotic perception, for improving lesion detection, anatomy tissue semantic parsing, cancer treatment planning, and surgical scene perception. 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.


This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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