Joint affine and deformable three-dimensional networks for brain MRI registration
Publication in refereed journal

香港中文大學研究人員
替代計量分析
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其它資訊
摘要Purpose

Volumetric medical image registration has important clinical significance. Traditional registration methods may be time-consuming when processing large volumetric data due to their iterative optimizations. In contrast, existing deep learning-based networks can obtain the registration quickly. However, most of them require independent rigid alignment before deformable registration; these two steps are often performed separately and cannot be end-to-end.

Methods

We propose an end-to-end joint affine and deformable network for three-dimensional (3D) medical image registration. The proposed network combines two deformation methods; the first one is for obtaining affine alignment and the second one is a deformable subnetwork for achieving the nonrigid registration. The parameters of the two subnetworks are shared. The global and local similarity measures are used as loss functions for the two subnetworks, respectively. Moreover, an anatomical similarity loss is devised to weakly supervise the training of the whole registration network. Finally, the trained network can perform deformable registration in one forward pass.

Results

The efficacy of our network was extensively evaluated on three public brain MRI datasets including Mindboggle101, LPBA40, and IXI. Experimental results demonstrate our network consistently outperformed several state-of-the-art methods with respect to the metrics of Dice index (DSC), Hausdorff distance (HD), and average symmetric surface distance (ASSD).

Conclusions

The proposed network provides accurate and robust volumetric registration without any pre-alignment requirement, which facilitates the end-to-end deformable registration.
著者Zhenyu Zhu, Yiqin Cao, Chenchen Qin, Yi Rao, Di Lin, Qi Dou, Dong Ni, Yi Wang
期刊名稱Medical Physics
出版年份2021
月份3
卷號48
期次3
出版社WILEY
頁次1182 - 1196
國際標準期刊號0094-2405
語言美式英語
關鍵詞affine alignment, brain MRI, convolutional neural networks, deformable image registra-tion, end-to-end registration

上次更新時間 2021-18-09 於 23:52