Radiomic features are typically used in machine learning models and are proven to generate reliable results when predicting tumor grade and responses to treatment. In Amir’s new paper, an innovative approach is proposed where dedicated in vivo experiments are used to correlate biological meaning to specific radiomic features.
Read all about it in:
A.L. Rifi, I. Dufait, C. El Aisati; M. De Ridder; K. Barbé. Interpretability and Repeatability of Radiomic Features: Applied on In Vivo Tumor Models. IEEE Transactions on Instrumentation and Measurement (2023).
