Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams

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

doi:10.1117/12.653025

Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

50 Scopus citations

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.

Original language	English
Title of host publication	Medical Imaging 2006
Subtitle of host publication	Image Processing
DOIs	https://doi.org/10.1117/12.653025
State	Published - 2006
Externally published	Yes
Event	Medical Imaging 2006: Image Processing - San Diego, CA, United States Duration: 13 Feb 2006 → 16 Feb 2006

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	6144 III
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2006: Image Processing
Country/Territory	United States
City	San Diego, CA
Period	13/02/06 → 16/02/06

Keywords

Cervical cancer
Cervicography images
Colposcopic image
Content-based indexing
Image segmentation
Medical image analysis

Access to Document

10.1117/12.653025

Cite this

Gordon, S., Zimmerman, G., Long, R., Antani, S., Jeronimo, J., & Greenspan, H. (2006). Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams. In Medical Imaging 2006: Image Processing Article 61444U (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6144 III). https://doi.org/10.1117/12.653025

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title = "Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams",

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.",

keywords = "Cervical cancer, Cervicography images, Colposcopic image, Content-based indexing, Image segmentation, Medical image analysis",

author = "Shiri Gordon and Gali Zimmerman and Rodney Long and Sameer Antani and Jose Jeronimo and Hayit Greenspan",

year = "2006",

doi = "10.1117/12.653025",

language = "English",

isbn = "0819464236",

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Gordon, S, Zimmerman, G, Long, R, Antani, S, Jeronimo, J & Greenspan, H 2006, Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams. in Medical Imaging 2006: Image Processing., 61444U, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 6144 III, Medical Imaging 2006: Image Processing, San Diego, CA, United States, 13/02/06. https://doi.org/10.1117/12.653025

Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams. / Gordon, Shiri; Zimmerman, Gali; Long, Rodney et al.
Medical Imaging 2006: Image Processing. 2006. 61444U (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6144 III).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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SN - 9780819464231

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2006

Y2 - 13 February 2006 through 16 February 2006

ER -

Content analysis of uterine cervix images: Initial steps towards content based indexing and retrieval of cervigrams

Abstract

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