The present invention relates to a system for predicting cerebral aneurysm rupture and the risk thereof by using a 3D cerebrovascular angiography image and a deep neural network. The system comprises: a learning data augmentation unit configured such that, in connection with a 3D cerebrovascular angiography image having lesion areas and rupture risk information marked by a specialist, the sizes of bounding boxes around the lesion areas are varied, and respective varied bonding boxes are cropped and flipped, thereby augmenting learning data; and a cerebral aneurysm rupture risk prediction unit which includes a deep neural network learning model for learning the augmented learning data and predicts and outputs the risk of cerebral aneurysm rupture by automatically detecting a lesion of a specific size or less, located in the entire circulatory system, on the basis of the deep neural network learning model from a 3D cerebrovascular angiography image input thereinto.
CEREBRAL ANEURYSM RUPTURE PREDICTION SYSTEM