Development of Subject-Specific Geometric Spine Model through Use of Automated Active Contour Segmentation and Kinematic Constraint-Limited Registration.

This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representati...

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Publicado en:Journal of Digital Imaging Vol. 24; no. 5; pp. 926 - 943
Autores principales: Strickland, Catherine, Aguiar, Daniel, Nauman, Eric, Talavage, Thomas
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Oct2011
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Oct2011
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      pub: Springer Nature
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        atl: Development of Subject-Specific Geometric Spine Model through Use of Automated Active Contour Segmentation and Kinematic Constraint-Limited Registration.
      aug:
        au:
          Strickland, Catherine
          Aguiar, Daniel
          Nauman, Eric
          Talavage, Thomas
        affil: School of Electrical and Computer Engineering, Purdue University, West Lafayette 47907-2035 USA
      sug:
        subj:
          Magnetic Resonance Imaging Methods
          Spine Radiography
          Image Processing, Computer Assisted Methods
          Intraoperative Care
          Automation
          Fluoroscopy
          Kinematics
          Validation Studies
          Human
          Sensitivity and Specificity
          Spine Anatomy and Histology
          Funding Source
      ab: This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representation of the image segmentation results. After determining errors within the segmentations, application of reliability theory allows the selection of active contour parameters to obtain best-fit segmentations from a stack of 2D images. The segmented images are then used in conjunction with C-arm fluoroscope images to simulate the result of intraoperative patient-specific model registration including patient and/or structure motion between preoperative and intraoperative scans. The results are validated through comparison of the error within the patient-specific model generated through use of the C-arm images with a model acquired directly from MRI images of the spine after motion. The results are applicable to the development of a wide variety of patient-specific geometric and biomechanical models.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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