Exploring feature-based approaches in PET images for predicting cancer treatment outcomes

  title={Exploring feature-based approaches in PET images for predicting cancer treatment outcomes},
  author={Issam El-Naqa and Perry Grigsby and A. Apte and E. Kidd and Eric D Donnelly and D. Khullar and S. Chaudhari and Deshan Yang and M. Schmitt and Richard Laforest and W. L. Thorstad and Joseph O. Deasy},
  journal={Pattern recognition},
  volume={42 6},
Accumulating evidence suggests that characteristics of pre-treatment FDG-PET could be used as prognostic factors to predict outcomes in different cancer sites. Current risk analyses are limited to visual assessment or direct uptake value measurements. We are investigating intensity-volume histogram metrics and shape and texture features extracted from PET images to predict patient's response to treatment. These approaches were demonstrated using datasets from cervix and head and neck cancers… CONTINUE READING
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