University of Cambridge > Talks.cam > Microsoft Research Cambridge, public talks > Energy Functionals: Choices and Consequences For Medical Image Segmentation

Energy Functionals: Choices and Consequences For Medical Image Segmentation

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending

Medical imaging continues to permeate the practice of medicine, but automated yet accurate segmentation and labeling of anatomical structures continues to be a major obstacle to computerized medical image analysis. Though there are numerous approaches for medical image segmentation, one in particular has gained increasing popularity: energy minimization-based techniques, and the large set of methods encompassed therein. With these techniques an energy function must be chosen, segmentations must be initialized, weights for competing terms of the energy functional must be tuned, and the resulting functional minimized. There are a lot of choices involved, and their consequences are not always clear. In this talk I explore the different consequences of these choices, and provide novel methods that attempt to overcome two of the more significant problems encountered: local minima and parameter settings.

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity