A new approach for tubular structure modeling and segmentation using graph-based techniques

  • Authors:
  • Jack H. Noble;Benoit M. Dawant

  • Affiliations:
  • Dept. of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN;Dept. of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN

  • Venue:
  • MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
  • Year:
  • 2011

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Abstract

In this work, a new approach for tubular structure segmentation is presented. This approach consists of two parts: (1) automatic model construction from manually segmented exemplars and (2) segmentation of structures in unknown images using these models. The segmentation problem is solved by finding an optimal path in a high-dimensional graph. The graph is designed with novel structures that permit the incorporation of prior information from the model into the optimization process and account for several weaknesses of traditional graph-based approaches. The generality of the approach is demonstrated by testing it on four challenging segmentation tasks: the optic pathways, the facial nerve, the chorda tympani, and the carotid artery. In all four cases, excellent agreement between automatic and manual segmentations is achieved.