A Knowledge-Based Approach to Soft Tissue Reconstruction of the Cervical Spine

For surgical planning in spine surgery, the segmentation of anatomical structures is a prerequisite. Past efforts focussed on the segmentation of vertebrae from tomographic data, but soft tissue structures have, for the most part, been neglected. Only sparse research work has been done for the spina...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2009-04, Vol.28 (4), p.494-507
Main Authors: Seifert, S., Wachter, I., Schmelzle, G., Dillmann, R.
Format: Article
Language:English
Subjects:
Algorithms
Anatomical structure
Automatic segmentation
Biological tissues
cervical soft tissue
Cervical Vertebrae - anatomy & histology
Cluster Analysis
generalized segmentation workflow
Humans
Image Interpretation, Computer-Assisted - methods
Image Processing, Computer-Assisted - methods
Intervertebral Disc - anatomy & histology
Magnetic Resonance Imaging
muscle reconstruction
Neck - anatomy & histology
Neck Muscles - anatomy & histology
Object recognition
Pattern Recognition, Automated - methods
Reconstruction algorithms
Reproducibility of Results
Spinal cord
Spine
Surface reconstruction
Surgery
Time Factors
Tomography
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Summary:For surgical planning in spine surgery, the segmentation of anatomical structures is a prerequisite. Past efforts focussed on the segmentation of vertebrae from tomographic data, but soft tissue structures have, for the most part, been neglected. Only sparse research work has been done for the spinal cord and the trachea. However, as far as the author is aware, there is no work on segmenting intervertebral discs. Therefore, a totally automatic reconstruction algorithm for the most relevant cervical structures is presented. It is implemented as a straightforward process, using anatomical knowledge which is, in concept, transferrable to other tissues of the human body. No seed points are required since the discs, as initial landmarks, are located via an object recognition approach. The spinal musculature is reconstructed by surface analysis on already segmented vertebrae, thus it can be taken into account in a biomechanical simulation. The segmentation results of our approach showed 91% accordance with expert segmentations and the computation time is less than 1 min on a standard PC. Since the presented system follows some general concepts this approach may also be considered as a step towards full body segmentation of the human.
ISSN:0278-0062
1558-254X
DOI:10.1109/TMI.2008.2004659