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Abstract #2646

Automatic Arterial Input Function Detection for Prostate Dynamic Contrast Enhanced MRI

Yingxuan Zhu1, Ming-Ching Chang2, Fiona M. Fennessy3, Sandeep Narendra Gupta4

1Dept. of EECS, Syracuse University, Syracuse, NY, United States; 2Vis. & Comp. Vision Lab, GE Global Research Center, Niskayuna, NY, United States; 3Dept. of Radiology, Brigham & Women's Hospital, Boston, MA, United States; 4Functional Imaging Lab, GE Global Research Center, Niskayuna, NY, United States


Dynamic Contrast Enhanced MRI has shown promise in non-invasive assessment of tumor vascular properties for prostate cancer staging and treatment monitoring. Accurate quantification from DCEMRI requires the determination of arterial input function. AIF is commonly measured manually by selecting an ROI, which is time consuming and subjective. Automated ways of measuring AIF would be useful. This is challenging because of extreme intensity non-uniformity. Therefore existing methods do not perform well. Here, we use both temporal and spatial information to determine the AIF. We validate our method on clinical data and compare our approach with expert user defined manual AIFs.

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