DIKU Bits: Introduction to medical image segmentation
Bulat Ibragimov, Ph.D and Assistant Professor of Machine Learning and Medical Imaging at the Department of Computer Science.
Medical image segmentation is the process of detecting and outlining objects, such as human organs and abnormal malformations in X-rays, computed tomography, magnetic resonance, and other image modalities. Medical image segmentation plays a critical role in disease diagnosis, treatment planning, and post-treatment monitoring. Automation of medical image segmentation has been of great interest to the research community for the last years. This lecture will introduce the technical concept of medical image segmentation, highlight the main clinical directions for image segmentation, and familiarize the audience with basic algorithms in medical image segmentation.
Zooming in on Bulat Ibragimov
Which courses do you teach? (BSc and MSc)
I teach Modeling and Analysis of Data (MAD) for BSc at DIKU, and Medical Image Analysis (MIA) for MSc at DIKU
Which technology/research/projects/startup are you excited to see the evolution of?
I am excited about the use of AI in image-guided procedures. I follow the progress of medical companies and strat-ups like Intuitive Surgical, Verb and Auris Health.