Paper Info
Title
A unified set of analysis tools for uterine cervix image segmentation.
Abstract
Segmentation is a fundamental component of many medical image-processing applications, and it has long been recognized as a challenging problem. In this paper, we report our research and development efforts on analyzing and extracting clinically meaningful regions from uterine cervix images in a large database created for the study of cervical cancer. In addition to proposing new algorithms, we also focus on developing open source tools which are in synchrony with the research objectives. These efforts have resulted in three Web-accessible tools which address three important and interrelated sub-topics in medical image segmentation, respectively: the Boundary Marking Tool (BMT), Cervigram Segmentation Tool (CST), and Multi-Observer Segmentation Evaluation System (MOSES). The BMT is for manual segmentation, typically to collect “ground truth” image regions from medical experts. The CST is for automatic segmentation, and MOSES is for segmentation evaluation. These tools are designed to be a unified set in which data can be conveniently exchanged. They have value not only for improving the reliability and accuracy of algorithms of uterine cervix image segmentation, but also promoting collaboration between biomedical experts and engineers which are crucial to medical image-processing applications. Although the CST is designed for the unique characteristics of cervigrams, the BMT and MOSES are very general and extensible, and can be easily adapted to other biomedical image collections.
Year
DOI
Venue
2010
10.1016/j.compmedimag.2010.04.002
Computerized Medical Imaging and Graphics
Keywords
DocType
Volume
Uterine cervix image,Image segmentation,Segmentation evaluation,Web-accessible system
Journal
34
Issue
ISSN
Citations 
8
0895-6111
1
PageRank 
References 
Authors
0.40
18
6
Name
Order
Citations
PageRank
Zhiyun Xue124522.97
L. Rodney Long253456.98
Sameer Antani31402134.03
Leif Neve4524.11
Yaoyao Zhu51106.77
George R. Thoma61207132.81