Early identification of ischemic stroke lesion regions plays a vital role in its treatments like thrombolytic therapy and patients’ recovery. Noncontrast computed tomography (ncCT) is the most widespread imaging modality in emergency departments. Unfortunately, it is extremely hard to distinguish the lesion from healthy tissue during the hyper‐acute phase of stroke. In this paper, a two‐stage convolutional neural network‐based method was proposed to identify the invisible ischemic stroke from ncCT.

中文翻译：

---

基于新型两阶段卷积神经网络模型的非对比CT隐性缺血性卒中识别

缺血性中风病灶区域的早期识别在其诸如溶栓治疗和患者康复的治疗中起着至关重要的作用。非对比计算机断层扫描（ncCT）是急诊科中使用最广泛的成像方式。不幸的是，在中风的超急性期很难将病变与健康组织区分开。本文提出了一种基于两步卷积神经网络的方法来从ncCT识别隐形缺血性卒中。