Title :
Automatic landmark detection in uterine cervix images for indexing in a content-retrieval system
Author :
Zimmerman, Gali ; Gordon, Shiri ; Greenspan, Hayit
Author_Institution :
Dept. of Biomed. Eng., Tel Aviv Univ.
Abstract :
This work is motivated by the need for visual information extraction and management in the growing field of content based image retrieval from medical archives. In particular it focuses on a unique medical repository of cervicographic images ("cervigrams") collected by the National Cancer Institute, National Institutes of Health, to study the evolution of lesions related to cervical cancer. The paper briefly presents a framework for cervigram segmentation and labelling, focusing on the identification of two anatomical landmarks: the cervix boundary and the os. These landmarks are identified based on their convexity, using adequate mathematical tools. Segmentation results are exemplified and an initial validation is carried out on a subset of 120 manually labelled cervigrams
Keywords :
cancer; gynaecology; image retrieval; image segmentation; medical image processing; automatic landmark detection; cervical cancer; cervicographic images; cervigram segmentation; cervigrams; cervix boundary; content-retrieval system; convexity; image retrieval; lesions; os; uterine cervix images; visual information extraction; Biomedical imaging; Cervical cancer; Content based retrieval; Content management; Data mining; Image retrieval; Indexing; Information management; Information retrieval; Lesions;
Conference_Titel :
Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-9576-X
DOI :
10.1109/ISBI.2006.1625176