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medicine nih nlim

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Web-based Annotation of Cervicographic Medical Images

High resolution

Visual examination for cervical caner

Design web-based application for textual and graphical annotation

Enhance indexing, storage and retrieval of cervicographic images

Open source survey application

Customizable

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

Contain positive and negative images

Word explanations

In-screen pop up via Lightbox

MySQL database for answer and time logs

Imported to Excel spreadsheets

Graphical response via an ellipse annotation tool

Supplements current textual response in web-based application

Encircle regions of interest on cervicographic images

Image-based query to databases

More precise searches and more consistent results

Research and educational collaboration

Visual data contains more information than textual descriptors

Scalable Vector Graphics (SVG) Two-dimensional graphics in XML Supported by most browsers

Embedded within HTML Supports scripting Web-based interaction

Intuitive, shallow learning curve

Two different designs Dynamic Centroid Static Centroid

Acknowledgements

Research advisor: George NagyResearch assistant: Kathryn CelentanoResearch assistant: Mike DingRCOS: Sean O' Sullivan, MoorthyNational Science FoundationNational Library of Medicine

Thank you

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