• DocumentCode
    62235
  • Title

    Iris-Based Medical Analysis by Geometric Deformation Features

  • Author

    Lin Ma ; Zhang, Dejing ; Naimin Li ; Yan Cai ; Wangmeng Zuo ; Kuanquan Wang

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin, China
  • Volume
    17
  • Issue
    1
  • fYear
    2013
  • fDate
    Jan. 2013
  • Firstpage
    223
  • Lastpage
    231
  • Abstract
    Iris analysis studies the relationship between human health and changes in the anatomy of the iris. Apart from the fact that iris recognition focuses on modeling the overall structure of the iris, iris diagnosis emphasizes the detecting and analyzing of local variations in the characteristics of irises. This paper focuses on studying the geometrical structure changes in irises that are caused by gastrointestinal diseases, and on measuring the observable deformations in the geometrical structures of irises that are related to roundness, diameter, and other geometric forms of the pupil and the collarette. Pupil- and collarette-based features are defined and extracted. A series of experiments are implemented on our experimental pathological iris database, including manual clustering of both normal and pathological iris images, manual classification by nonspecialists, manual classification by individuals with a medical background, classification ability verification for the proposed features, and disease recognition by applying the proposed features. The results prove the effectiveness and clinical diagnostic significance of the proposed features and a reliable recognition performance for automatic disease diagnosis. Our research results offer a novel systematic perspective for iridology studies and promote the progress of both theoretical and practical work in iris diagnosis.
  • Keywords
    biomechanics; deformation; diseases; eye; feature extraction; image classification; medical image processing; collarette-based feature; disease recognition; gastrointestinal disease diagnosis; iridology study; iris anatomy modeling; iris diagnosis; iris geometric deformation feature; iris image clasification; iris variation characteristics; iris-based medical analysis; normal iris image clustering; pathological iris database; pathological iris image clustering; pupil geometric feature; pupil-based feature; Diseases; Iris; Iris recognition; Manuals; Medical diagnostic imaging; Pathology; Collarette-based feature; disease recognition; iris geometric deformation feature; pupil-based feature; Cluster Analysis; Databases, Factual; Female; Humans; Image Interpretation, Computer-Assisted; Iris; Linear Models; Male; Pattern Recognition, Automated; Stomach Diseases; Support Vector Machines;
  • fLanguage
    English
  • Journal_Title
    Biomedical and Health Informatics, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    2168-2194
  • Type

    jour

  • DOI
    10.1109/TITB.2012.2222655
  • Filename
    6339069