# Deep learning for automated cerebral aneurysm detection on computed tomography images

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-learning-for-automated-cerebral-aneurysm-detection-on-computed-tomography/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Xilei Dai,Lixiang Huang,Yi Qian,Shuang Xia,Winston Chong,Junjie Liu,Antonio Di Ieva,Xiaoxi Hou,Chubin Ou |
| Citations | 90 |
| DOI | 10.1007/s11548-020-02121-2 |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3006125542 |
| PMID | 32056126 |
| Type | article |
| Year | 2020 |

## Paper authors

- [Yi Qian](https://scholariq.org/researchers/yi-qian/)

## Paper journal

- [International Journal of Computer Assisted Radiology and Surgery](https://scholariq.org/journals/international-journal-of-computer-assisted-radiology-and-surgery/)

## Paper primary topic

- [Intracranial Aneurysms: Treatment and Complications](https://scholariq.org/topics/intracranial-aneurysms-treatment-and-complications/)

## Paper topics

- [Intracranial Aneurysms: Treatment and Complications](https://scholariq.org/topics/intracranial-aneurysms-treatment-and-complications/)
- [Intracerebral and Subarachnoid Hemorrhage Research](https://scholariq.org/topics/intracerebral-and-subarachnoid-hemorrhage-research/)
- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.