End-to-end semantic segmentation of personalized deep brain structures for non-invasive brain stimulation
End-to-end semantic segmentation of personalized deep brain structures for non-invasive brain stimulation
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DOI：
10.1016/j.neunet.2020.02.006
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发表时间：
2020-05-01
期刊：
影响因子：
7.8
通讯作者：
Hirata, Akimasa
中科院分区：
文献类型：
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作者：
Rashed, Essam A.;Gomez-Tames, Jose;Hirata, Akimasa
脑深部区域的电刺激或调制通常用于治疗几种神经系统疾病的临床程序中。特别地，经颅直流电刺激（tDCS）被广泛用作通过附接到头皮的电极施加的负担得起的临床应用。然而，由于解剖结构的复杂性和受试者间的高度变异性，很难确定不同脑区域中电场（EF）的量和分布。个性化tDCS是一种新兴的临床手术，用于耐受电极导联以实现准确定位。该过程由从诸如MRI的解剖图像生成的计算头部模型引导。通过仿真研究，可以计算分割头部模型中的EF分布。因此，快速、准确、可行地分割不同的脑结构将为定制的tDCS研究带来更好的调整。在这项研究中，提出了一种用于脑深部分割的单编码器多解码器卷积神经网络。所提出的架构被训练为使用T1加权MRI分割七个深部脑结构。将网络生成的模型与使用半自动方法构建的参考模型进行比较，并且网络生成的模型呈现出高匹配，特别是在丘脑（Dice系数（DC）= 94.70%）、尾状核（DC = 91.98%）和壳核（DC = 90.31%）结构中。生成模型和参考模型中tDCS期间的电场分布彼此匹配良好，表明其在临床实践中的潜在有用性。(c)2020爱思唯尔有限公司保留所有权利。
Electro-stimulation or modulation of deep brain regions is commonly used in clinical procedures for the treatment of several nervous system disorders. In particular, transcranial direct current stimulation (tDCS) is widely used as an affordable clinical application that is applied through electrodes attached to the scalp. However, it is difficult to determine the amount and distribution of the electric field (EF) in the different brain regions due to anatomical complexity and high inter-subject variability. Personalized tDCS is an emerging clinical procedure that is used to tolerate electrode montage for accurate targeting. This procedure is guided by computational head models generated from anatomical images such as MRI. Distribution of the EF in segmented head models can be calculated through simulation studies. Therefore, fast, accurate, and feasible segmentation of different brain structures would lead to a better adjustment for customized tDCS studies.In this study, a single-encoder multi-decoders convolutional neural network is proposed for deep brain segmentation. The proposed architecture is trained to segment seven deep brain structures using T1-weighted MRI. Network generated models are compared with a reference model constructed using a semi-automatic method, and it presents a high matching especially in Thalamus (Dice Coefficient (DC) = 94.70%), Caudate (DC = 91.98%) and Putamen (DC = 90.31%) structures. Electric field distribution during tDCS in generated and reference models matched well each other, suggesting its potential usefulness in clinical practice. (c) 2020 Elsevier Ltd. All rights reserved.