Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
Automatic rigging and animation of 3D characters
ACM SIGGRAPH 2007 papers
Automatic segmentation of head structures on fetal MRI
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
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Recent improvements in MRl scanners have enabled the acquisition of spatially consistent 3D images of the fetus. While recent works focused on the fetal brain segmentation, important outcome could be obtained from the segmentation of the whole fetal body envelope, such as accurate fetal weight estimation. In this paper, we propose to segment this envelope using a semi-automatic approach. MRI images were acquired using the Steady State Free Precession sequence. Taking advantage ofthe T2-weighting of this sequence, a set of fetal structures is identified and a simplified model of the fetal skeleton is instantiated in the images. An articulated model of a generic fetus is then registered in the images to initialize the fetal envelope segmentation and optimized using graph-cuts to refine the segmentation. Promising and robust results were obtained on a set of nine volumes.