Research >> Fast Model-Based Segmentation

 

Fast Model-Based Segmentation

 

Given a volumetric image and a model of the object to be segmented,
segment the desired object efficiently. New well-posed algorithms
will allow for the real-time segmentation of the prostate from medical
CT images, yielding the possibility of image-guided radiotherapy.

 

Faculty: Daniel Freedman
Former Student: Tao Zhang

 

 

Publications:

D. Freedman and T. Zhang. Interactive graph cut based segmentation with shape priors. IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) , volume 1, pages 755-762, 2005. [ pdf ] [ bib ]


D. Freedman , R. J. Radke, T. Zhang, Y. Jeong, D. M. Lovelock, and G. T. Y. Chen. Model-based segmentation of medical imagery by matching distributions. IEEE Transactions on Medical Imaging , 24(3):281-292, 2005. [ pdf ] [ bib ]

 

D. Freedman , R.J. Radke, T. Zhang, Y. Jeong, and G.T.Y Chen. Model-based multi-object segmentation via distribution matching. Proceeding of the Third IEEE Workshop on Articulated and Nonrigid Motion (in conjunction with IEEE CVPR 2004) , June 27, 2004, Baltimore, MD. [ pdf ] [ bib ]

 

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