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Abstract #0819

Prospective Image Registration for Automated Scan Prescription of Follow-Up Knee Images

Janet Goldenstein1,2, Joseph Schooler1, Jason C. Crane1, Eugene Ozhinsky1,2, Julio Carballido-Gamio1, Sharmila Majumdar1

1Department of Radiology and Biomedical Imaging, UC San Francisco, San Francisco, CA, United States; 2Joint Graduate Group in Bioengineering, UC Berkeley/UC San Francisco, San Francisco, CA, United States

Consistent scan prescription for MRI of the knee is very important for accurate comparison and quantitative analysis of images in a longitudinal study. This study demonstrates the feasibility of using a mutual information based method to register MR images of the knee without segmentation and automatically determine the follow-up scan prescription. This registration method is performed only on the distal femur and is not affected by the proximal tibia or soft tissues. Results show an improvement with registration in the coefficient of variation for cartilage thickness, cartilage volume, and T2 relaxation measurements.