Content analysis of uterine cervix images: initial steps toward content based indexing and retrieval of cervigrams

Shiri Gordon; Gali Zimmerman; Rodney Long; Sameer Antani; Jose Jeronimo M.D.; Hayit Greenspan

doi:10.1117/12.653025

15 March 2006 Content analysis of uterine cervix images: initial steps toward content based indexing and retrieval of cervigrams

Shiri Gordon, Gali Zimmerman, Rodney Long, Sameer Antani, Jose Jeronimo M.D., Hayit Greenspan

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61444U (2006) https://doi.org/10.1117/12.653025
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

This work is motivated by the need for visual information extraction and management in the growing field of medical image archives. In particular the work focuses on a unique medical repository of digital cervicographic images ("Cervigrams") collected by the National Cancer Institute (NCI) in a longitudinal multi-year study carried out in Guanacaste, Costa Rica. NCI together with the National Library of Medicine (NLM) is developing a unique Web-based database of the digitized cervix images to study the evolution of lesions related to cervical cancer. Such a database requires specific tools that can analyze the cervigram content and represent it in a way that can be efficiently searched and compared. We present a multi-step scheme for segmenting and labeling regions of medical and anatomical interest within the cervigram, utilizing statistical tools and adequate features. The multi-step structure is motivated by the large diversity of the images within the database. The algorithm identifies the cervix region within the image. It than separates the cervix region into three main tissue types: the columnar epithelium (CE), the squamous epithelium (SE), and the acetowhite (AW), which is visible for a short time following the application of acetic acid. The algorithm is developed and tested on a subset of 120 cervigrams that were manually labeled by NCI experts. Initial segmentation results are presented and evaluated.

Citation Download Citation

Shiri Gordon, Gali Zimmerman, Rodney Long, Sameer Antani, Jose Jeronimo M.D., and Hayit Greenspan "Content analysis of uterine cervix images: initial steps toward content based indexing and retrieval of cervigrams", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61444U (15 March 2006); https://doi.org/10.1117/12.653025

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