Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.

Journal: La Radiologia medica

PMID: 39666223

Abstract

PURPOSE: Assessment of the stability of intracranial aneurysms is important in the clinic but remains challenging. The aim of this study was to construct a deep learning model (DLM) to identify unstable aneurysms on computed tomography angiography (CTA) images.

Authors

Lu Zeng

East China University of Science and Technology, Shanghai, China.
Li Wen
Yang Jing

Huiying Medical Technology Co., Ltd, Dongsheng Science and Technology Park, Haidian District, Beijing, China.
Jing-Xu Xu

Department of Research Collaboration, Research and Development (R&D) center, Beijing Deepwise and League of Philosophy Doctor (PHD) Technology Co., Ltd, Beijing, China.
Chen-Cui Huang

AI Lab, Deepwise and League of PhD Technology Co. LTD, Beijing, China.
Dong Zhang

Institute of Acoustics, Nanjing University, Nanjing 210093, China.
Guang-Xian Wang

Department of Radiology, Banan Hospital, Chongqing Medical University, Chongqing, 401320, China. wgxlove1234@163.com.

Keywords

Adult Aged Aneurysm, Ruptured Computed Tomography Angiography Deep Learning Female Humans Intracranial Aneurysm Male Middle Aged Neural Networks, Computer Retrospective Studies Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (39666223)

Assessment of the stability of intracranial aneurysms using a deep learning model based on computed tomography angiography.

Abstract

Authors

Keywords

External Resources

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