Challenges in automated detection of cervical intraepithelial neoplasia

Srinivasan, Yeshwanth; Yang, Shuyu; Nutter, Brian; Mitra, Sunanda; Phillips, B.; Long, L. Rodney

doi:10.1117/12.710051

Cited by 3 publications

(1 citation statement)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Therefore, automatic image segmentation and region type recognition are initial steps necessary for CBIR. Our ongoing research on this topic has been reported in [11][12][13][14]. The prototype CBIR system operates on a subset of the cervigram database in which important regions were manually marked and labeled by dozens of NCI medical experts, with the assistance of our Boundary Marking Tool (BMT).…”

Section: Introductionmentioning

confidence: 99%

A web-accessible content-based cervicographic image retrieval system

Xue

Long

Jerónimo³

et al. 2008

SPIE Proceedings

View full text Add to dashboard Cite

Content-based image retrieval (CBIR) is the process of retrieving images by directly using image visual characteristics. In this paper, we present a prototype system implemented for CBIR for a uterine cervix image (cervigram) database. This cervigram database is a part of data collected in a multi-year longitudinal effort by the National Cancer Institute (NCI), and archived by the National Library of Medicine (NLM), for the study of the origins of, and factors related to, cervical precancer/cancer. Users may access the system with any Web browser. The system is built with a distributed architecture which is modular and expandable; the user interface is decoupled from the core indexing and retrieving algorithms, and uses open communication standards and open source software. The system tries to bridge the gap between a user's semantic understanding and image feature representation, by incorporating the user's knowledge. Given a user-specified query region, the system returns the most similar regions from the database, with respect to attributes of color, texture, and size. Experimental evaluation of the retrieval performance of the system on "groundtruth" test data illustrates its feasibility to serve as a possible research tool to aid the study of the visual characteristics of cervical neoplasia.

show abstract

Section: Introductionmentioning

confidence: 99%