Radiological features of brain hemorrhage through automated segmentation from computed tomography in stroke and traumatic brain injury.

Bradley J MacIntosh,Qinghui Liu,Till Schellhorn,Mona K Beyer,Inge Rasmus Groote, Pål C Morberg, Joshua M Poulin, Maiken N Selseth,Ragnhild C Bakke, Aina Naqvi,Amir Hillal,Teresa Ullberg,Johan Wassélius,Ole M Rønning,Per Selnes,Espen S Kristoffersen,Kyrre Eeg Emblem,Karoline Skogen,Else C Sandset,Atle Bjørnerud

Frontiers in neurology（2023）

引用 0|浏览9

暂无评分

摘要

An open-source segmentation tool was used to visualize hemorrhage locations across multiple data sources and revealed quantitative hemorrhage site differences. The automated total hemorrhage volume estimate correlated with a per-participant hemorrhage cluster count. ROC results were moderate-to-high. The VIOLA-AI tool had promising results and might be useful for various types of intracranial hemorrhage.

查看译文

关键词

computed tomography, intracerebral hemorrhage, stroke, traumatic brain injury, segmentation, deep learning

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要