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Abstract #3013

An Image Searching Engine to Utilize Past Clinical Data for the Future Diagnosis

Andreia V. Faria1, Shoko Yoshida1, Kenichi Oishi1, Kanako Sato1, Argye Hillis2, MIchael I. Miller3, Susumu Mori1

1Radiology, Johns Hopkins University, Baltimore, MD, United States; 2Neurology, Johns Hopkins Hospital, Baltimore, MD, United States; 3Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States

We report our attempt to develop a technology to structurize image features and facilitate image searching. The structurization was based on automated parcellation of the entire brain into 211 structures using T1-WIs and high-dimensional normalization method. We tested if the structurized anatomical data actually captured the anatomical features in a population with atrophy at different degrees and locations by comparing the results with trained clinicians evaluation. We explored the data and tested individual classifications using PCA and discriminant analysis. The structurization of image data through image-vector conversion was effective, and provides opportunities to mine clinical database for medical decision support