medicine nih nlim

1. Web-based Annotation of
Cervicographic Medical Images

2.  High resolution
 Visual
examination for
cervical caner

3.  Design web-based application for textual and
graphical annotation
 Enhance indexing, storage and retrieval of
cervicographic images

4.  Open source survey
application
 Customizable

5.  19 Question system with
logic tree for each
question
 5 Cervigrams per survey
 Reference image guided
showing positive and
negative
 Login-in system for user
anonymity
 Enlarge for all images

7.  Contain positive and
negative images
 Word explanations
 In-screen pop up via
Lightbox

8.  MySQL database
for answer and
time logs
 Imported to
Excel
spreadsheets

9.  Graphical response
via an ellipse
annotation tool
 Supplements
current textual
response in web-
based application
 Encircle regions of
interest on
cervicographic
images

10.  Image-based query to databases
 More precise searches and more consistent results
 Research and educational collaboration
 Visual data contains more information than textual
descriptors

11.  Scalable Vector Graphics (SVG)
 Two-dimensional graphics in XML
 Supported by most browsers
 Embedded within HTML
 Supports scripting
 Web-based interaction

12.  Intuitive, shallow learning curve
 Two different designs
 Dynamic Centroid
 Static Centroid

13. Acknowledgements
Research advisor: George Nagy
Research assistant: Kathryn Celentano
Research assistant: Mike Ding
RCOS: Sean O' Sullivan, Moorthy
National Science Foundation
National Library of Medicine
Thank you