Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

Jan Egger; Christopher Nimsky

doi:10.1117/12.2209039

6 April 2016 Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

Jan Egger, Christopher Nimsky

Author Affiliations +

Proceedings Volume 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment; 97871G (2016) https://doi.org/10.1117/12.2209039
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

Abstract

Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCut - algorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99±5.03% and a HD of 18.91±7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation – with an average time of less than six minutes (5.77±0.73) – is significantly shorter than a pure manual outlining.

Citation Download Citation

Jan Egger and Christopher Nimsky "Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures", Proc. SPIE 9787, Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, 97871G (6 April 2016); https://doi.org/10.1117/12.2209039

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