Evaluation of an automated intracranial aneurysm detection and rupture analysis approach using cascade detection and classification networks

• Published in: Computerized medical imaging and graphics Vol. 102; p. 102126
• Main Authors: Wu, Ke, Gu, Dongdong, Qi, Peihong, Cao, Xiaohuan, Wu, Dijia, Chen, Lei, Qu, Guoxiang, Wang, Jiayu, Pan, Xianpan, Wang, Xuechun, Chen, Yuntian, Chen, Lizhou, Xue, Zhong, Lyu, Jinhao
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.12.2022
• Subjects: Aged; Aneurysm, Ruptured - diagnostic imaging; Angiography, Digital Subtraction - methods; Cascade detection model; Cerebral Angiography - methods; Feature pyramid network; Humans; Internal Medicine; Intracranial aneurysm; Intracranial Aneurysm - diagnostic imaging; Other; Rupture analysis; Sensitivity and Specificity; Cascade detection model; Feature pyramid network; Rupture analysis; Intracranial aneurysm
• ISSN: 0895-6111; 1879-0771; 1879-0771
• DOI: 10.1016/j.compmedimag.2022.102126

Intracranial aneurysm is commonly found in human brains especially for the elderly, and its rupture accounts for a high rate of subarachnoid hemorrhages. However, it is time-consuming and requires special expertise to pinpoint small aneurysms from computed tomography angiography (CTA) images. Deep l...