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An online segmentation tool for cervicographic image analysis.
Cervicography is an important visual screening method for cervical cancer prevention. Automatic segmentation of clinically significant regions in acquired images may provide valuable assistance toward research in cervical cancer detection. This paper presents a Web-accessible cervicographic image segmentation system that incorporates several novel segmentation algorithms developed for particular tissue types and landmarks. The system combines the advantages of two commonly used programming languages, Matlab and Java. It relieves the research groups in academic institutes from the heavy burden of re-developing the sophisticated segmentation algorithms originally implemented in Matlab, while allowing medical experts to evaluate the segmentation algorithms using, perhaps, their own image data acquired at remote locations. It offers attractive properties of flexibility, extensibility and Web-accessibility in a prototype image processing application. The system is integrated with other applications that have been developed for uterine cervix image analysis at the U.S. National Library of Medicine. The architecture and concept of this system are generalizable and can be applied to different medical image processing tasks.