• DocumentCode
    881656
  • Title

    Computer analysis of computed tomography scans of the lung: a survey

  • Author

    Sluimer, Ingrid ; Schilham, Arnold ; Prokop, Mathias ; Van Ginneken, Bram

  • Author_Institution
    Image Sci. Inst., Univ. Med. Center Utrecht, Netherlands
  • Volume
    25
  • Issue
    4
  • fYear
    2006
  • fDate
    4/1/2006 12:00:00 AM
  • Firstpage
    385
  • Lastpage
    405
  • Abstract
    Current computed tomography (CT) technology allows for near isotropic, submillimeter resolution acquisition of the complete chest in a single breath hold. These thin-slice chest scans have become indispensable in thoracic radiology, but have also substantially increased the data load for radiologists. Automating the analysis of such data is, therefore, a necessity and this has created a rapidly developing research area in medical imaging. This paper presents a review of the literature on computer analysis of the lungs in CT scans and addresses segmentation of various pulmonary structures, registration of chest scans, and applications aimed at detection, classification and quantification of chest abnormalities. In addition, research trends and challenges are identified and directions for future research are discussed.
  • Keywords
    computerised tomography; diagnostic radiography; image classification; image registration; image resolution; image segmentation; lung; medical image processing; chest abnormality detection; computed tomography scans; computer analysis; image; image classification; image registration; lung; medical imaging; near isotropic submillimeter resolution; pulmonary structure segmentation; review; thoracic radiology; Artificial neural networks; Attenuation; Biomedical imaging; Cancer; Computed tomography; Diseases; Image segmentation; Lungs; Medical diagnostic imaging; Radiology; Airway disease; CT; chest; computer-aided diagnosis; emphysema quantification; interstitial lung disease; literature review; literature survey; lung cancer; nodule characterization; nodule detection; nodule size measurements; pulmonary embolism; registration; segmentation; Algorithms; Animals; Artificial Intelligence; Humans; Image Enhancement; Imaging, Three-Dimensional; Information Storage and Retrieval; Lung; Lung Diseases; Pattern Recognition, Automated; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Tomography, X-Ray Computed;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/TMI.2005.862753
  • Filename
    1610745