论文标题
VOL2Brain：全新的在线脑部MRI分析的新在线管道
vol2Brain: A new online Pipeline for whole Brain MRI analysis
论文作者
论文摘要
对于临床和研究环境来说，用于MR大脑图像分析的自动且可靠的定量工具是非常宝贵的资源。在过去的几年中，基于标签融合和最近深入学习的成功技术，该领域取得了许多进步。但是，很少有专门设计的来在多尺度上提供密集的解剖标签，并处理诸如白质病变之类的大脑解剖学改变。在这项工作中，我们提出了一条全自动管道（VOL2BRAIN），用于整个大脑分割和分析，该管道将大脑（n> 100）的标签（n> 100）稳健，同时对白质病变的存在稳健。这条新管道是我们以前的Volbrain管道的演变，它显着扩展了可以分析的区域数量。我们提出的方法是基于快速的多尺度多ATLAS标签融合技术，具有系统的误差校正能够在几分钟内提供准确的体积信息。我们已经在平台Volbrain（www.volbrain.upv.es）中部署了新管道，这已经被证明是与全球用户共享我们技术的一种有效的有效方式
Automatic and reliable quantitative tools for MR brain image analysis are a very valuable resources for both clinical and research environments. In the last years, this field has experienced many advances with successful techniques based on label fusion and more recently deep learning. However, few of them have been specifically designed to provide a dense anatomical labelling at multiscale level and to deal with brain anatomical alterations such as white matter lesions. In this work, we present a fully automatic pipeline (vol2Brain) for whole brain segmentation and analysis which densely labels (N>100) the brain while being robust to the presence of white matter lesions. This new pipeline is an evolution of our previous volBrain pipeline that extends significantly the number of regions that can be analyzed. Our proposed method is based on a fast multiscale multi-atlas label fusion technology with systematic error correction able to provide accurate volumetric information in few minutes. We have deployed our new pipeline within our platform volBrain (www.volbrain.upv.es) which has been already demonstrated to be an efficient and effective manner to share our technology with users worldwide
