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33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)   pp. 139-144
A Mammography Database and View System for the African American Patients
Shani Ross, Howard University, Washington DC
O'tega Ejofodomi, Howard University, Washington DC
Ahmed Jendoubi, Howard University, Washington DC
Mohamed Chouikha, Howard University, Washington DC
Ben Lo, Georgetown University, Washington DC
Paul Wang, Howard University, Washington DC
Jianchao Zeng, Howard University, Washington DC

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AIPR.2004.3
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Abstract
In this research, we have obtained and scanned mammography films (within the last ten years) of African American women treated at Howard University Hospital Radiology Department, constructed a database using the digitized mammography images, and developed an image viewing system to display these digital mammograms. The images are scanned with the high resolution Kodak LS85 laser scanner. The digital mammography database is powered by MySQL and PHP. It also has a web-based search engine (with secure access) so that the information can be made accessible to all medical team members. The image viewing software, D-Viewer, is coded in C# and is intended to help medical professionals view and retrieve large data sets in near real time. We have already digitized 260 cases (one case per patient, twenty to forty films per case). We also have developed a MySQL-based image database, and a PHP-based web-search engine to retrieve cases that have masses (benign or malignant) or calcifications (benign or malignant). This database has been evaluated by medical professionals and the experimental results obtained so far are very promising (high image qualities, fast access time). We are currently developing an image content-based retrieval function for the database system in order to provide improved search capability for the medical professionals.
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Citation:  Shani Ross, O'tega Ejofodomi, Ahmed Jendoubi, Mohamed Chouikha, Ben Lo, Paul Wang, Jianchao Zeng, "A Mammography Database and View System for the African American Patients," aipr, pp. 139-144,  33rd Applied Imagery Pattern Recognition Workshop (AIPR'04),  2004