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Abstract #2599

Effect of ISODATA Dimensionality on Spatiotemporal Evolution of Ischemic Brain Injury in Acute Ischemic Stroke

Jerry S. Cheung1, Enfeng Wang1,2, Xiaoying Wang3, Phillip Zhe Sun1

1Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, MGH & Harvard Medical School, Charlestown, MA 02129, United States; 2Department of Radiology, 3rd Affiliated Hospital, Zhengzhou University, China, People's Republic of; 3Neuroprotection Research Laboratory, Department of Radiology & Neurology, MGH & Harvard Medical School, Charlestown, MA 02129, United States

Iterative self-organizing data analysis technique algorithm (ISODATA) has been increasingly used to classify multi-parametric data for delineation of heterogeneous ischemic damage. Our study compared two different dimensionalities (1D vs. 2D) of ISODATA signature vector in ISODATA parameter space to segment evolving PWI/DWI mismatch. We showed that accurate delineation of PWI/DWI mismatch with 1D signature vector outperformed conventional 2D analysis, and offer a useful means to identify ischemic penumbra.