Segmentation of trabecular bones from vertebral bodies in volumetric CT spine images

Authors:
Melih S. Aslan;Asem Ali;Ben Arnold;Rachid Fahmi;Aly A. Farag;Ping Xiang
Affiliations:
University of Louisville, Computer Vision and Image Processing Laboratory, Louisville, KY;University of Louisville, Computer Vision and Image Processing Laboratory, Louisville, KY;Image Analysis Inc., Columbia, KY;University of Louisville, Computer Vision and Image Processing Laboratory, Louisville, KY;University of Louisville, Computer Vision and Image Processing Laboratory, Louisville, KY;Image Analysis Inc., Columbia, KY
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

Citing 3
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Abstract

We present a 3D segmentation technique of trabecular (cancellous) bones in CT images of Vertebral bodies (VBs). In order to be used for Bone Mineral Density (BMD) measurements, the cortical and trabecular bones are subsequently segmented using graph cuts method and local volume growing methods separately. In the final step, we measure our segmentation accuracy for each method. Validity was analyzed using ground truths of data sets and the European Spine Phantom (ESP). Preliminary results are very encouraging and a reproducibility of the results was achieved for 16 data sets. The average segmentation error is below 2.0% for both methods.