Content-based indexing and retrieval of uterine cervix images

Gali Zimermman; Shiri Gordon; Hayit Greenspan

Content-based indexing and retrieval of uterine cervix images

Gali Zimermman, Shiri Gordon, Hayit Greenspan

Research output: Contribution to conference › Paper › peer-review

6 Scopus citations

Abstract

This work is motivated by the need for visual information management in the growing field of digital libraries and by the increasing information retrieval demands in the domains of medical imaging and telemedicine. We focus on a large database of digitized 35mm slides of the uterine cervix collected by the National Cancer Institute (NCI), National Institutes of Health (NIH), to study the evolution of lesions related to cervical cancer. As a first step towards this goal we focus on the problem of intelligently labeling (segmenting) regions of medical interest within the cervigram image. In this paper we use statistical tools for the segmentation of three tissue types of interest.

Original language	English
Pages	181-184
Number of pages	4
State	Published - 1 Dec 2004
Externally published	Yes
Event	2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings - Tel-Aviv, Israel Duration: 6 Sep 2004 → 7 Sep 2004

Conference

Conference	2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings
Country/Territory	Israel
City	Tel-Aviv
Period	6/09/04 → 7/09/04

ASJC Scopus subject areas

Electrical and Electronic Engineering
Electronic, Optical and Magnetic Materials

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Content-based indexing and retrieval of uterine cervix images",

abstract = "This work is motivated by the need for visual information management in the growing field of digital libraries and by the increasing information retrieval demands in the domains of medical imaging and telemedicine. We focus on a large database of digitized 35mm slides of the uterine cervix collected by the National Cancer Institute (NCI), National Institutes of Health (NIH), to study the evolution of lesions related to cervical cancer. As a first step towards this goal we focus on the problem of intelligently labeling (segmenting) regions of medical interest within the cervigram image. In this paper we use statistical tools for the segmentation of three tissue types of interest.",

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AU - Zimermman, Gali

AU - Gordon, Shiri

AU - Greenspan, Hayit

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AB - This work is motivated by the need for visual information management in the growing field of digital libraries and by the increasing information retrieval demands in the domains of medical imaging and telemedicine. We focus on a large database of digitized 35mm slides of the uterine cervix collected by the National Cancer Institute (NCI), National Institutes of Health (NIH), to study the evolution of lesions related to cervical cancer. As a first step towards this goal we focus on the problem of intelligently labeling (segmenting) regions of medical interest within the cervigram image. In this paper we use statistical tools for the segmentation of three tissue types of interest.

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M3 - Paper

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T2 - 2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel, Proceedings

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ER -

Content-based indexing and retrieval of uterine cervix images

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

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