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Proceedings Paper

Shape priors for segmentation of the cervix region within uterine cervix images
Author(s): Shelly Lotenberg; Shiri Gordon; Hayit Greenspan
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Paper Abstract

The work focuses on a unique medical repository of digital Uterine Cervix images ("Cervigrams") collected by the National Cancer Institute (NCI), National Institute of Health, in longitudinal multi-year studies. NCI together with the National Library of Medicine is developing a unique web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Tools are needed for the automated analysis of the cervigram content to support the cancer research. In recent works, a multi-stage automated system for segmenting and labeling regions of medical and anatomical interest within the cervigrams was developed. The current paper concentrates on incorporating prior-shape information in the cervix region segmentation task. In accordance with the fact that human experts mark the cervix region as circular or elliptical, two shape models (and corresponding methods) are suggested. The shape models are embedded within an active contour framework that relies on image features. Experiments indicate that incorporation of the prior shape information augments previous results.

Paper Details

Date Published: 11 March 2008
PDF: 11 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69141N (11 March 2008); doi: 10.1117/12.770075
Show Author Affiliations
Shelly Lotenberg, Tel Aviv Univ. (Israel)
Shiri Gordon, Tel Aviv Univ. (Israel)
Hayit Greenspan, Tel Aviv Univ. (Israel)


Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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