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Querying Breast Cancer Image Databases

Multimedia Presentation Launch Presentation
 
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Produced by:
Microsoft Research

10/07/2005

Description: 
Breast cancer remains a leading cause of cancer deaths among women in many parts of the world. In the United States alone, over forty thousand women die of the disease each year. Mammography is currently the most cost-effective method for early detection of breast cancer. Alternative medical imaging approaches such as ultrasound or MRI could be more effective than mammography at detecting cancers or evaluating malignancy in certain types of women. A database with images from multiple technologies like mammograms, MRI, PET, and ultrasound will enable research into the effectiveness and usefulness of each technique at cancer screening and the determination of malignancy. We created this database with Microsoft SQL Server and will be using it to develop a tool that will use it to provide doctors with a web-based query tool to access the data via web services. Doctors will also be able to find cases similar to a current patient thereby improving the accuracy of the diagnosis. This database will be an invaluable tool for the improvement of computer aided detection (CAD) techniques by providing quality data sets, the storage of feature sets for comparison, a tool for the complex combination of features through spatial relationships and across images, and built-in statistical analysis. We will develop a pictorial query specification system for this tool that will enable users to specify queries by identifying the desired features, shapes, or characteristics and specifying the spatial relationship between them using distance and direction. Additionally, the secure data storage and retrieval enables long-distance, electronic image transmission (telemammography/teleradiology) for clinical consultations. The database will match images from the same patient, thus improving the capability of comparing images through time, which will enable the determination of extremely early cancerous indicators, and thus hopefully improve the cancer survival rate.

Speaker(s):
Hanan Samet, Computer Science Department, University of Maryland

Runtime:00:41:14

Rating:TV-G


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