• DocumentCode
    607735
  • Title

    Characterization of lung nodules

  • Author

    Kaya, Ahmet ; Can, Ahmet Burak

  • Author_Institution
    Bilgisayar Muhendisligi Bolumu, Hacettepe Univ., Ankara, Turkey
  • fYear
    2013
  • fDate
    24-26 April 2013
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Recognition of lung nodules and classification of them as benign and malignent are very important in diagnosis of lung cancer. Present methods on nodule classification generally concentrate on defining nodule as either benign or malignent but do not consider radiographic descriptors that play important role on classification of small-sized lung nodules. In this paper, features extracted from nodule images to denote radiographic descriptors are studied. With the results from classification and dimension reduction approaches, which images features truly denote radiographic descriptors is analyzed.
  • Keywords
    cancer; diagnostic radiography; feature extraction; image classification; lung; medical image processing; dimension reduction; feature extraction; lung cancer diagnosis; lung nodule classification; lung nodule recognition; radiographic descriptor; Biomedical imaging; Cancer; Computed tomography; Educational institutions; Lungs; Radiology; Support vector machines; classification; dimension reduction; image processing; small pulmonary nodules;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications Applications Conference (SIU), 2013 21st
  • Conference_Location
    Haspolat
  • Print_ISBN
    978-1-4673-5562-9
  • Electronic_ISBN
    978-1-4673-5561-2
  • Type

    conf

  • DOI
    10.1109/SIU.2013.6531396
  • Filename
    6531396