Automatic risk prediction of intracranial aneurysm on CTA image with convolutional neural networks and radiomics analysis.

ABSTRACT:

Background

Intracranial aneurysm (IA) is a nodular protrusion of the arterial wall caused by the localized abnormal enlargement of the lumen of a brain artery, which is the primary cause of subarachnoid hemorrhage. Accurate rupture risk prediction can effectively aid treatment planning, but conventional rupture risk estimation based on clinical information is subjective and time-consuming.

Methods

We propose a novel classification method based on the CTA images for differentiating aneurysms that are prone to rupture. The main contribution of this study is that the learning-based method proposed in this study leverages deep learning and radiomics features and integrates clinical information for a more accurate prediction of the risk of rupture. Specifically, we first extracte

SUBMITTER: Xie Y 

PROVIDER: S-EPMC10345199 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature