Interactive Separation of Segmented Bones in CT Volumes Using Graph Cut

Authors:
Lu Liu;David Raber;David Nopachai;Paul Commean;David Sinacore;Fred Prior;Robert Pless;Tao Ju
Affiliations:
Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130;Washington University in St. Louis, St. Louis, USA MO 63130
Venue:
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
Year:
2008

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Abstract

We present a fast, interactive method for separating bones that have been collectively segmented from a CT volume. Given user-provided seed points, the method computes the separation as a multi-way cut on a weighted graph constructed from the binary, segmented volume. By properly designing and weighting the graph, we show that the resulting cut can accurately be placed at bone-interfaces using only a small number of seed points even when the data is noisy. The method has been implemented with an interactive graphical interface, and used to separate the 12 human foot bones in 10 CT volumes. The interactive tool produced compatible result with a ground-truth separation, generated by a completely manual labelling procedure, while reducing the human interaction time from a mean of 2.4 hours per volume in manual labelling down to approximately 18 minutes.