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Abstract #2833

Standardization of MRI as Pre-Processing Method for Machine Learning Based Segmentation

Robert T Wujek1,2 and Kathleen M Schmainda3

1Biomedical Engineering, The Medical College of Wisconsin, Milwaukee, WI, United States, 2Biomedical Engineering, Marquette University, Milwaukee, WI, United States, 3Biophysics, The Medical College of Wisconsin, Milwaukee, WI, United States

In this study, standardization methods are used to pre-process brain MRI to generate a machine learning dataset for tumor segmentation. This method was chosen for previously documented repeatability properties as compared to more widely used normalization methods, which could potentially lead to a more generalized segmentation model. When applied to the publicly available BRATS dataset, the standardization methods performed equally as well as the normalization method used in this study, which supports further analysis of the methods beyond the highly controlled BRATS dataset.

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