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MICCAI
2006
Springer

An Energy Minimization Approach to the Data Driven Editing of Presegmented Images/Volumes

10 years 2 months ago
An Energy Minimization Approach to the Data Driven Editing of Presegmented Images/Volumes
Fully automatic, completely reliable segmentation in medical images is an unrealistic expectation with today's technology. However, many automatic segmentation algorithms may achieve a near-correct solution, incorrect only in a small region. For these situations, an interactive editing tool is required, ideally in 3D, that is usually left to a manual correction. We formulate the editing task as an energy minimization problem that may be solved with a modified version of either graph cuts or the random walker 3D segmentation algorithms. Both algorithms employ a seeded user interface, that may be used in this scenario for a user to seed erroneous voxels as belonging to the foreground or the background. In our formulation, it is unnecessary for the user to specify both foreground and background seeds.
Leo Grady, Gareth Funka-Lea
Added 14 Nov 2009
Updated 14 Nov 2009
Type Conference
Year 2006
Where MICCAI
Authors Leo Grady, Gareth Funka-Lea
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