Integrating automatic and interactive brain tumor segmentation

This paper integrates automatic segmentation based on supervised learning with an interactive multi-scale watershed segmentation method. The combined method automatically provides an initial segmentation that applies the building blocks that the user can use in the interactive method. Thereby the two approaches are seamlessly integrated and the combined method can be used on the full range of problems from very easy to very difficult segmentation tasks resulting in different levels of interaction needed. The method is evaluated for the segmentation of brain tumors.

[1]  Hubert Cardot,et al.  Cooperation of color pixel classification schemes and color watershed: a study for microscopic images , 2002, IEEE Trans. Image Process..

[2]  Guido Gerig,et al.  Automatic Brain and Tumor Segmentation , 2002, MICCAI.

[3]  Max A. Viergever,et al.  Multiscale Segmentation of Three-Dimensional MR Brain Images , 1999, International Journal of Computer Vision.

[4]  Timothy F. Cootes,et al.  Active Shape Models-Their Training and Application , 1995, Comput. Vis. Image Underst..

[5]  Paul A. Yushkevich,et al.  Multiscale deformable model segmentation and statistical shape analysis using medial descriptions , 2002, IEEE Transactions on Medical Imaging.

[6]  Wiro J Niessen,et al.  Interactive multi-scale watershed segmentation of tumors in MR brain images , 2001 .

[7]  Ole Fogh Olsen,et al.  Multi-Scale Watershed Segmentation , 1997, Gaussian Scale-Space Theory.

[8]  Bram van Ginneken,et al.  Supervised segmentation by iterated contextual pixel classification , 2002, Object recognition supported by user interaction for service robots.

[9]  Alejandro F. Frangi,et al.  Model-based segmentation of cardiac and vascular images , 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

[10]  Guido Gerig,et al.  Robust Estimation for Brain Tumor Segmentation , 2003, MICCAI.

[11]  R. Kikinis,et al.  Automated segmentation of MR images of brain tumors. , 2001, Radiology.

[12]  I. Vanhamel,et al.  A hierarchical Markovian model for multiscale region-based classification of multispectral images , 2003, IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, 2003.

[13]  Mads Nielsen,et al.  Non-linear Diffusion for Interactive Multi-scale Watershed Segmentation , 2000, MICCAI.