Title :
3D Deformable Surfaces with Locally Self-Adjusting Parameters - A Robust Method to Determine Cell Nucleus Shapes
Author :
Keuper, Margret ; Schmidt, Thorsten ; Padeken, Jan ; Heun, Patrick ; Palme, Klaus ; Burkhardt, Hans ; Ronneberger, Olaf
Author_Institution :
Comput. Sci. Dept., Freiburg Univ., Freiburg, Germany
Abstract :
When using deformable models for the segmentation of biological data, the choice of the best weighting parameters for the internal and external forces is crucial. Especially when dealing with 3D fluorescence microscopic data and cells within dense tissue, object boundaries are sometimes not visible. In these cases, one weighting parameter set for the whole contour is not desirable. We are presenting a method for the dynamic adjustment of the weighting parameters, that is only depending on the underlying data and does not need any prior information. The method is especially apt to handle blurred, noisy, and deficient data, as it is often the case in biological microscopy.
Keywords :
image segmentation; medical image processing; nucleus; shape recognition; 3D deformable surfaces; 3D fluorescence microscopic data; biological data segmentation; biological microscopy; determine cell nucleus shapes; locally selfadjusting parameters; robust method; Biology; Covariance matrix; Force; Image segmentation; Microscopy; Shape; Three dimensional displays; active contour; cell segmentation; parameter estimation;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.552