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Abstract #2451

Mean or Extremum? Comparison of Two Strategies to Extract Orientation-Dependent Texture Features in Radiomics Studies

Jing Zhang1, Yang Song1, Yu-dong Zhang2, Xu Yan3, Yefeng Yao1, and Guang Yang1
1Shanghai Key Laboratory of Magnetic Resonance, Department of Physics, East China Normal University, shanghai, China, 2Department of Radiology, The First Affiliated Hospital with Nanjing Medical University,, Nanjing, China, 3MR Scientific Marketing, Siemens Healthcare, shanghai, China

Texture features plays an important role in radiomics. To make the texture features rotation-invariant, pyradiomics computes the texture features along all directions and use their mean values. In this study, we demonstrated that maximum and minimum values of these features along different directions, which is also rotation-invariant, may provide added value to radiomics studies. We trained models using mean, maximum and minimum values of texture features along different directions to classify clinically significant (CS) prostate cancer (PCa) and non-CS PCa on PROSTATEx dataset. We found that using extremum instead of mean texture features improved the performance of model.

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