The promise of AI in medical imaging lies not only in higher automation, productivity and standardization, but also in an unprecedented use of quantitative data beyond the limits of human cognition. This will support more accurate and more personalized diagnostics and therapies along multitude of disease pathways. Today, artificial intelligence already plays an important role in the everyday practice of image acquisition, processing and interpretation. In this talk, I provide example clinical applications where AI plays an integral role. These applications range from automated scanning, detection of anatomical structures, intelligent image registration and reformatting to predicting therapy outcome based on multimodal data.
Ali Kamen received BSc in EE and MSc in BME from Sharif University of Technology. He received PhD in ECE from the University of Miami. After graduation he joined Siemens Corporate Research in Princeton NJ, where he has been leading technology development teams in the areas of personalized healthcare and image guided procedures. Currently he leads initiatives in translating artificial intelligence based technologies to differentiated value-creating clinical products. Additionally, Dr. Kamen leads active collaborations with a number of universities including the University of Pennsylvania, Cleveland Clinic, Harvard Medical School, Johns Hopkins, and University of Iowa, with more than $5M awarded from a number of NIH-funded grants. He has more than 100 refereed publications (with h-Index 38), and more than 100 US and international patents (granted and pending) primarily in the areas of medical image computing, computational modeling, and image guided procedures. He is recognized as Siemens Inventor of the Year in 2015. He is also a Fellow of American Institute for Medical and Biological Engineers.