Automatic segmentation of the ribs, the vertebral column, and the spinal canal in pediatric computed tomographic images.

We propose methods to perform automatic identification of the rib structure, the vertebral column, and the spinal canal in computed tomographic (CT) images of pediatric patients. The segmentation processes for the rib structure and the vertebral column are initiated using multilevel thresholding and...

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Publicado en:Journal of Digital Imaging Vol. 23; no. 3; pp. 301 - 323
Autores principales: Banik S, Rangayyan RM, Boag GS
Formato: diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Jun2010
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jun2010
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      pub: Springer Nature
      place: New York, New York
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        atl: Automatic segmentation of the ribs, the vertebral column, and the spinal canal in pediatric computed tomographic images.
      aug:
        au:
          Banik S
          Rangayyan RM
          Boag GS
        affil: Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada T2N 1N4.
      sug:
        subj:
          Cervical Vertebrae Radiography
          Image Processing, Computer Assisted Methods
          Lumbar Vertebrae Radiography
          Ribs Radiography
          Spinal Canal Radiography
          Thoracic Vertebrae Radiography
          Algorithms
          Automation
          Cervical Vertebrae Pathology
          Confidence Intervals
          Evaluation Research
          Funding Source
          Human
          Lumbar Vertebrae Pathology
          Ribs Pathology
          Spinal Canal Pathology
          Thoracic Vertebrae Pathology
          Tomography, X-Ray Computed
      ab: We propose methods to perform automatic identification of the rib structure, the vertebral column, and the spinal canal in computed tomographic (CT) images of pediatric patients. The segmentation processes for the rib structure and the vertebral column are initiated using multilevel thresholding and the results are refined using morphological image processing techniques with features based on radiological and anatomical prior knowledge. The Hough transform for the detection of circles is applied to a cropped edge map that includes the thoracic vertebral structure. The centers of the detected circles are used to derive the information required for the opening-by-reconstruction algorithm used to segment the spinal canal. The methods were tested on 39 CT exams of 13 patients; the results of segmentation of the vertebral column and the spinal canal were assessed quantitatively and qualitatively by comparing with segmentation performed independently by a radiologist. Using 13 CT exams of six patients, including a total of 458 slices with the vertebra from different sections of the vertebral column, the average Hausdorff distance was determined to be 3.2 mm with a standard deviation (SD) of 2.4 mm; the average mean distance to the closest point (MDCP) was 0.7 mm with SD = 0.6 mm. Quantitative analysis was also performed for the segmented spinal canal with three CT exams of three patients, including 21 slices with the spinal canal from different sections of the vertebral column; the average Hausdorff distance was 1.6 mm with SD = 0.5 mm, and the average MDCP was 0.6 mm with SD = 0.1 mm.
      pubtype: Academic Journal
      doctype:
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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