Ischemic Stroke Lesion Segmentation Using Multi-Plane Information Fusion
Ischemic Stroke Lesion Segmentation Using Multi-Plane Information Fusion
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DOI：
10.1109/access.2020.2977415
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发表时间：
2020-03
期刊：
影响因子：
3.9
通讯作者：
Long Zhang;Ruoning Song;Yuanyuan Wang;Chuang Zhu;Jun Liu;Jie Yang;Lian Liu
中科院分区：
文献类型：
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作者：
Long Zhang;Ruoning Song;Yuanyuan Wang;Chuang Zhu;Jun Liu;Jie Yang;Lian Liu
弥散加权磁共振成像(DWI)对急性缺血性卒中敏感，是一种常见的卒中诊断方法。然而，诊断结果依赖于神经科医生的视觉观察，不同的医生在不同的情况下可能会有不同的视觉观察。而人工分割通常是一个耗时且主观的过程。发病至血栓清除的时间对急性缺血性卒中患者的预后有显著影响。治疗时间越短，预后越好。为此，我们提出了一种新的框架来快速、自动地分割DWI上的缺血性卒中病变。本文的主要贡献有三个方面：一是设计了一个检测与分割网络(DSN)来解决这两类数据不均衡的问题；二是提出了一种三分支DSN结构，分别用于提取不同的平面特征；三是提出了一种多平面融合网络(MPFN)，旨在使最终的预测更加准确。在ISLES2015 SSIS DWI序列数据集上的大量实验证明了该分割方法的优越性。骰子达到62.2%，灵敏度达到71.7%。
Diffusion-weighted magnetic resonance imaging (DWI) is sensitive to acute ischemic stroke and is a common diagnostic method for the stroke. However, the diagnostic result relies on the visual observation of neurologists which may vary from doctor to doctor under different circumstance. And manual segmentation is often a time-consuming and subjective process. The time from onset to thrombus removal has a significant impact on the prognosis of patients with acute ischemic stroke. The shorter the time, the better the prognosis. For this purpose we present a novel framework to quickly and automatically segment the ischemic stroke lesions on DWI. We mainly have three contributions: firstly, we design a detection and segmentation network (DSN) to solve the two kinds of data imbalance; secondly, we propose a triple-branch DSN architecture, used for extracting different plane feature respectively; thirdly, we propose a multi-plane fusion network (MPFN), which aims to make final prediction more accurate. Extensive experiments on ISLES2015 SSIS DWI sequence dataset demonstrate the superiority of our proposed segmentation method. The dice reached 62.2% and the sensitivity reached 71.7%.