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Content Analysis of
Uterine Cervix Images (Cervigrams)
for Indexing in CBIR systems
Overview
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 studies carried out in Guanacaste,
Costa Rica and the united states. 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. The work is
part of an on-going effort towards the creation of a content-based image
retrieval (CBIR) system for the cervicographic images. Such a system
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. The
multi-step structure is motivated by the large diversity of the images within
the database. The algorithm initially identifies the cervix region within the image and
allocates the cervix boundary and the os landmarks. It than performs
illumination correction and intensity normalization of the images across the
data-set. This step is shown to improve successive segmentation results.
Tissue segmentation is handled next and the cervix region is segmented 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.
Areas of acetowhitening correlate with higher nuclear density and
are of clinical signifficance.
Results for the different steps within this scheme are evaluated on different
sets of manually labeled cervigrams, for which the markings of one to twenty
experts are available. When an image is marked by more than one expert
different analysis schemes based on the output of the
STAPLE algorithm (
Warfield et.al - TMI 2004) are presented.
Publications
 | S. Gordon, PhD Thesis, submitted on July 2009. Automatic
content analysis of uterine cervix images using computerized tools.
[pdf] |
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| S. Gordon, S. Lotenberg, R. Long, S. Antani, J. Jeronimo for the
NIH-ASCCP Research Group and H. Greenspan. “Evaluation of Uterine Cervix
Segmentations using Ground Truth from Multiple Experts”. Accepted for
publication in Computerized Medical Imaging and Graphics (CMIG), December
2008. |
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| H. Greenspan, S. Gordon, G. Zimmerman, S. Lotenberg, J. Jeronimo, S.
Antani and R. Long. “Automatic Detection of Anatomical Landmarks in
Uterine Cervix Images”. Accepted for publication in IEEE Transaction on
Medical Imaging (TMI), August 2008 |
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| S. Lotenberg , S. Gordon and H.
Greenspan. "Shape priors for
segmentation of the cervix region within uterine cervix images".
Journal of Digital Imaging, accepted for publication 2008. |
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| S. Lotenberg , S. Gordon and H.
Greenspan. "Shape priors for
segmentation of the cervix region within uterine cervix images". In
Proc. of SPIE medical imaging, 2008.
[pdf] |
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| S.Gordon
and H. Greenspan. "Segmentation of non-convex regions within uterine
cervix images". In Proc. of
IEEE International Symposium on Biomedical Imaging, 2007. [pdf] |
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S. Lotenberg, S. Gordon,
R. Long, S. Antani,
J. Jeronimo and H. Greenspan. "Automatic
evaluation of uterine cervix segmentations".
In Proc. of SPIE medical imaging, 2007. [pdf] |
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H. Dvir, S. Gordon and H. Greenspan.
"Illumination
correction for content analysis in uterine cervix images".
In Proc. of
IEEE WS
Mathematical Methods in Biomedical Image Analysis (MMBIA),
Computer Vision and Pattern Recognition
Workshop (CVPRW06), page 95,
2006.
[pdf] |
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G. Zimmerman, S.
Gordon and H. Greenspan.
"Automatic
landmark detection in uterine cervix images for indexing in a
content-retrieval system".
In Proc. of IEEE International Symposium on Biomedical Imaging, pages
1348-1351, 2006. [pdf] |
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S.
Gordon, G. Zimmerman, R. Long, S. Antani, J.Jeronimo and H. Greenspan.
"Content
analysis of uterine cervix images: Initial steps towards content based
indexing and retrieval of cervigrams".
In Proc. of SPIE medical imaging,
volume 6144, pages 1549-1556,
2006.
[pdf] |
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G.
Zimmerman and H. Greenspan. "Automatic
detection of specular reflections in uterine cervix images".
In
Proc. of SPIE Medical Imaging, volume 6144, pages 2037- 2045,
2006. [pdf] |
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S. Gordon , G. Zimmerman and H. Greenspan. "Image segmentation of uterine
cervix images for indexing in PACS", In Proc. of 17th IEEE Symposium
on Computer-Based Medical Systems, CBMS 2004. Bethesda, MD, 2004.
[pdf] |
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G. Zimmerman, S. Gordon and H. Greenspan. "Content-based indexing and
retrieval of uterine cervix images", In Proc. of 23rd IEEE Convention of
Electrical and Electronics Engineers in Israel 2004, pages 181-185, Tel-Aviv,
Israel, 2004. [pdf] |
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