论文标题
放射科医生级的中风分类在非对比度CT扫描中使用深U-NET
Radiologist-level stroke classification on non-contrast CT scans with Deep U-Net
论文作者
论文摘要
缺血性中风和计算机断层扫描上颅内出血的分割对于中风的研究和治疗至关重要。在本文中，我们使用非对比度CT修改了U-NET CNN体系结构，以解决中风识别问题。我们将提出的DL模型应用于历史患者数据，还进行了涉及十位经验丰富的放射科医生的临床实验。我们的模型在历史数据上取得了很大的成果，并且在十个中的七位放射科医生的表现明显优于七位放射科医生，同时与剩余的三个相当。
Segmentation of ischemic stroke and intracranial hemorrhage on computed tomography is essential for investigation and treatment of stroke. In this paper, we modified the U-Net CNN architecture for the stroke identification problem using non-contrast CT. We applied the proposed DL model to historical patient data and also conducted clinical experiments involving ten experienced radiologists. Our model achieved strong results on historical data, and significantly outperformed seven radiologist out of ten, while being on par with the remaining three.
