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Abstract #1727

Addition of peritumoral area improves T1-weighted texture-based prediction of glioblastoma multiforme progression

George Zenzerovich1 and Tim Q Duong2
1Radiology, Stony Brook University, Stony Brook, NY, United States, 2Stony Brook University, Stony Brook, NY, United States

Texture features obtained from peritumoral area of diagnostic MR image of Glioblastoma Multiforme were used to improve texture based prediction of tumor progression. The peritumoral area was drawn and examined then derived texture features were added to conventional model to improve performance.

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