3D region growing integrating adaptive shape prior
Jean-Loïc Rose, Chantal Revol-Muller, Jean‐Baptiste Langlois, Marc F Janier, Christophe Odet · 2008
We propose an automated region growing integrating adaptive shape prior in order to segment biomedical images. In our work, the segmentation method is improved by taking into account a shape reference model by non-linear way. Thus, the proposed method is driven by statistical data computed from the evolving region and by a priori shape information given by the model. An improvement of the method is proposed by adapting automatically the degree of integration of shape prior for each pixel of the image. The proposed method was applied for segmenting 3D micro-CT image of mouse skull in the framework of small animal imaging. The method gives promising results and appears to be well adapted to the context.