“In my research, I have developed methods to estimate motions from medical image sequences, so-called intra-interventional medical images.” Niklas Gunnarsson, WASP industrial PhD student at Elekta and Uppsala universitet is defending the doctoral thesis “Motion Estimation from Temporally and Spatially Sparse Medical Image Sequences” on December 5th at 9:15. What are the main findings of your doctoral thesis? “In my research, I have developed methods to estimate motions from medical image sequences, so-called intra-interventional medical images. Due to the limitation of the acquisition time, the images often suffer from sparse temporal and spatial resolution. My methods rely on classical methods of medical image registration and dynamic models in combination with the latest developments in deep learning.” In what way can your research be of importance to our society in the future? “Motion modeling from intra-interventional medical images helps professionals with guidance and support during ongoing treatments. One example appears in the radiation therapy domain, where 2D cine-MRI images are acquired during a treatment session. A reliable 3D motion model is essential to providing accurate estimates of the treatment outcomes and a necessary tool to support more advantageous procedures, like controlling the beam during the treatment session, a so-called online adaptive workflow.” Join the public defense on December 5th at 9:15 at Ångström Laboratory, 101195, Heinz-Otto Kreiss, Uppsala University. Supervisors: Thomas Schön, Jens Sjölund and Peter Kimstrand #wasp #waspgraduateschool #phd More information about the defense and link to thesis: https://lnkd.in/ds9QqrEE
