Technical Program

Paper Detail

Paper:	SU-AM-PS4.1
Session:	Image Segmentation, Retrieval and Analysis
Time:	Sunday, April 9, 10:50 - 12:10
Presentation:	Poster
Title:	Automatic Landmark Detection in Uterine Cervix Images for Indexing in a Content-Retrieval System
Authors:	Gali Zimmerman; Tel-Aviv University
	Shiri Gordon; Tel-Aviv University
	Hayit Greenspan; Tel-Aviv University
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.

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