Building skeleton models via 3-D medial surface/axis thinning algorithms
CVGIP: Graphical Models and Image Processing
Markov random field modeling in image analysis
Markov random field modeling in image analysis
Spinal crawlers: deformable organisms for spinal cord segmentation and analysis
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
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The assessment of anomalies in the scoliotic spine using Magnetic Resonance Imaging (MRI) is an essential task during the planning phase of a patient's treatment and operations. Due to the pathologic bending of the spine, this is an extremely time consuming process as an orthogonal view onto every vertebra is required. In this article we present a system for computer-aided assessment (CAA) of anomalies in 3-D MRI images of the spine relying on curved planar reformations (CPR). We introduce all necessary steps, from the pre-processing of the data to the visualization component. As the core part of the framework is based on a segmentation of the spinal cord we focus on this. The proposed segmentation method is an iterative process. In every iteration the segmentation is updated by an energy based scheme derived from Markov random field (MRF) theory. We evaluate the segmentation results on public available clinical relevant 3-D MRI data sets of scoliosis patients. In order to assess the quality of the segmentation we use the angle between automatically computed planes through the vertebra and planes estimated by medical experts. This results in a mean angle difference of less than six degrees.