Automatic differentiation of ruptured and unruptured intracranial aneurysms on computed tomography angiography based on deep learning and radiomics

Abstract Objectives Rupture of intracranial aneurysm is very dangerous, often leading to death and disability. In this study, deep learning and radiomics techniques were used to automatically detect and differentiate ruptured and unruptured intracranial aneurysms. Materials and methods 363 ruptured...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Junbang Feng, Rong Zeng, Yayuan Geng, Qiang Chen, Qingqing Zheng, Fei Yu, Tie Deng, Lei Lv, Chang Li, Bo Xue, Chuanming Li
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	SpringerOpen 2023-05-01
Sarja:	Insights into Imaging
Aiheet:	Computed tomography angiography Intracranial aneurysm Rupture Deep learning Radiomics
Linkit:	https://doi.org/10.1186/s13244-023-01423-8
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