Jerry S. Cheung1, Enfeng Wang1,2, Xiaoying Wang3, Phillip Zhe Sun1
1Athinoula A. Martinos Center
for Biomedical Imaging, Department of Radiology,
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.