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Monday, October 14 • 2:00pm - 2:30pm
Artificial Intelligence in Medicine with Examples in Digital Pathology and Computed Tomography Perfusion

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Artificial Intelligence (AI) in medicine is a highly expanding field, with applications ranging from surgery robotics, visualization, segmentation, diagnostics and beyond.  Worldwide we see a strong increase in the amount of medical data and information collected for diagnostic purposes every year.  However the number of human specialists, like radiologists and pathologists are not increasing correspondingly.  Specifically, we have a large increase in tissue samples, histological stains, at the laboratories throughout the western world, but the number of trained pathologists is reported to be decreasing.     At the same time, there has been a tremendous development within different branches of AI in recent years, for a wide range of applications. Especially, the development of deep neural network (DNN) architectures have showed important results throughout the world of image processing and computer vision, and has also made its way into medical image applications. In this talk we will focus on some of the challenges and possibilities of AI in medicine through some examples from digital pathology and Computed Tomography (CT) perfusion. In digital pathology, histological stains are scan by microscopy scanners producing high resolution whole slide images (WSI) of 400 times magnification. We will look at examples of AI and DNN architectures used for analysis of whole slide images from urinary bladder cancer and melanoma, for the purpose of tissue classification and segmentation as well as diagnostics, predicting cancer grade and extracting prognostic information. CT perfusion of the head is fast and painless, and it produce 4D image data, i.e. 3D + time.  It is a useful technique for measuring blood flow to the brain, and an important tool to assess patients with cerebral stroke.  In this talk we will look at some AI approaches using image processing and DNN for analysing CT perfusion for stroke patients. "

avatar for Kjersti Engan

Kjersti Engan

Professor of Electrical Engineering and Computer Science, University of Stavanger, Norway
Kjersti Engan is a full professor at the Electrical Engineering and Computer Science department at the University of Stavanger (UiS). She received the BE degree in electrical engineering from Bergen University College in 1994 and the M.Sc. and Ph.D degrees in 1996 and 2000 respectively... Read More →

Monday October 14, 2019 2:00pm - 2:30pm CDT
BRC 103

Attendees (5)