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
Link To Document :
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