• DocumentCode
    1428434
  • Title

    Texture analysis for classification of cervix lesions

  • Author

    Ji, Qiang ; Engel, John ; Craine, Eric

  • Author_Institution
    Dept. of Comput. Sci., Nevada Univ., Reno, NV, USA
  • Volume
    19
  • Issue
    11
  • fYear
    2000
  • Firstpage
    1144
  • Lastpage
    1149
  • Abstract
    This paper presents a generalized statistical texture analysis technique for characterizing and recognizing typical, diagnostically most important, vascular patterns relating to cervical lesions from colposcopic images. The contributions of the research include: (1) the introduction of a generalized texture analysis technique based on the combination of the conventional statistical and structural textural analysis approaches by using a statistical description of geometric primitives; (2) the introduction of a set of textural measures that capture the specific characteristics of cervical textures as perceived by humans. An experimental study with real images demonstrated the feasibility and promise of the proposed approach in discriminating between cervical texture patterns indicative of different stages of cervical lesions.
  • Keywords
    cancer; gynaecology; image classification; image texture; medical image processing; optical images; statistical analysis; cervix lesions classification; colposcopic images; geometric primitives; lesion stage; medical diagnostic imaging; texture analysis; typical diagnostically most important vascular patterns; Character recognition; Humans; Image analysis; Image recognition; Image texture analysis; Lesions; Pathology; Pattern analysis; Pattern recognition; Testing; Female; Humans; Uterine Cervical Neoplasms;
  • fLanguage
    English
  • Journal_Title
    Medical Imaging, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0278-0062
  • Type

    jour

  • DOI
    10.1109/42.896790
  • Filename
    896790