Intracranial Large Vessel Severe Stenosis and Occlusion Detection Based on Vision Transformer Fusion Model from Multi-parametric MRI

Motivation: Traditionally, large vessel severe stenosis and occlusion (LVSSO) detection based on CTA needs contrast agent exposure. It is important to develop a LVSSO detection approach using contrast agent-free MR images that can achieve results comparable to clinical doctors. Goal(s): To develop a new fusion algorithm that can achieve the accuracy comparable to clinical diagnostic levels. Approach: A new fusion algorithm model based on vision transformer was developed. A total of 380 patients were enrolled in the current study. Results: The proposed model achieved an AUC of 0.963 and an accuracy of 94.7%. Impact: The proposed model achieved satisfactory accuracy for LVSSO detection, i.e. 94.7%, indicating that the performance of the proposed model has reached the clinical diagnosis level.