Improved hypertensive stroke classification based on multi-scale feature fusion of head axial CT angiogram and multimodal learning.

Journal: Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PMID: 38688073

Abstract

PURPOSE: Strokes are severe cardiovascular and circulatory diseases with two main types: ischemic and hemorrhagic. Clinically, brain images such as computed tomography (CT) and computed tomography angiography (CTA) are widely used to recognize stroke types. However, few studies have combined imaging and clinical data to classify stroke or consider a factor as an Independent etiology.

Authors

  • Shuting Liu
    School of Control Science and Engineering, Dalian University of Technology, Dalian, Liaoning 116024, China. Electronic address: liushuting@mail.dlut.edu.cn.
  • Pan Qin
    Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, Liaoning, China.
  • Zeyuan Wang
    School of Computer Science, The University of Sydney, Australia; Real-World Study Group, Medicinovo Inc., China.
  • Yi Liu
    Department of Interventional Therapy, Ningbo No. 2 Hospital, Ningbo, China.

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