Grading brain astrocytoma using convolutional neural network: contrast-enhanced T1 and susceptibility-weighted imaging

Susceptibility-weighted imaging (SWI) has shown its potential to discriminate between high-grade and low-grade astrocytoma. In this study, we developed a fully automatic diagnosis system for astrocytoma grading by using convolutional neural network with contrast-enhanced T1-weighted images and SWI, separately or jointly, as input data. The results show that the model with both imaging modalities as input data provides high accuracy in astrocytoma grading and is potentially helpful for clinical diagnosis.