Detection and characterization of abnormal vascular patterns in automated cervical image analysis

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4292 LNCS - II, Issue , 2006, Pages 627-636

  Li, Wenjing ^a   Poirson, Allen ^a  

^a STI Med Systems   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE SYSTEMS; COLOR; COMPUTER AIDED DIAGNOSIS; IMAGE ANALYSIS; INFORMATION ANALYSIS; SIGNAL DETECTION;

CERVICAL CANCER SCREENING; CERVICAL IMAGES; CERVICAL INTRAEPITHELIAL NEOPLASIA (CIN); PUNCTATION VESSELS; VASCULAR PATTERNS;

PATTERN RECOGNITION;

EID: 33845441616     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11919629_63     Document Type: Conference Paper

References (7)

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2. Ji, Q., Engel, J., and Craine, E.: Texture analysis for classification of cervix lesions. IEEE Trans. Med. Imaging 19(11) (2000) 1144-1149
3. Srinivasan, Y., Hernes, D., Tulpule, B., Yang, S. et al.: A probabilistic approach to segmentation and classification of neoplasia in uterine cervix images using color and geometric features, in Proc.of SPIE Medical Imaging, 5747. (2005) 995-1003
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