medical imaging markup viewer (keynote)
DESCRIPTION
A new world of digital diagnostic capabilities has been made possible with the advances in medical imaging. These advances promoted communication and cooperation between several distinct entities to create standards and models that can be used in the entire industry to improve the quality of the final service offered to users. Despite the growing quality in digital images, they are not enough alone. That is, it is required that a human clinician elaborates a report contained his medical opinion about specific traits found in the obtained images. These structured reports comprise mostly free text annotations that have not been explored yet. Therefore, the development of a standard data model for structured reports and image annotations is a crucial step in the process of improving medical imaging technologies and servicesTRANSCRIPT
MIM ViewerMedical Imaging Markup Viewer
Pedro Lopes | [email protected] | PDEI - TAEI2: Medical Imaging | July 24th, 2009
Acknowledgement: The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement nº 200754,the GEN2PHEN project.
Outline
‣ Introduction
‣ Problem
‣ Data Model
‣ Data Exchange
‣ Architecture
‣ MIM Viewer
‣ Conclusion
‣ Future work
Introduction
‣ Medical Imaging deals with large amounts of information
‣ Images are a great media for trait detection
- However...
‣ Sometimes images are not enough...
- Textual reports are valuable additions
Image Annotations
Problem
‣ How to deal with annotations?
‣ Storage
- Complex information
‣ Generic, scalable, flexible
- What data model?
‣ Exchange
- How to implement this data model?
- Reduce the complex annotations to a simple file?
Data Model [Complete]
Data Model [General Annotation]
Main annotation information
Data Model [Image]
DICOM image information
Data Model [Markup]
Text and image additions
Data exchange file [XML]
Architecture
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MIM Viewer
‣ Prototype application
- Only the viewer component
‣ 3 main modules
- Annotation list
‣ XML file containing the analyzed annotations
- DICOM
‣ Image proxy
- Viewer
‣ Main image visualization application
MIM Viewer [DEMO]
Conclusions
‣ Image Annotation is enormously complex
‣ No industry standard
- caBIG group is pushing this data model...
‣ Deploy the entire architecture is a cumbersome task
MSc work?
Future work
‣ Enhance and implement framework data model
‣ Improve data exchange format
‣ Develop MIM Engine and MIM Writer
‣ Create richer MIM Viewer
- Focus on web user interface
Thank You!
Questions?