干旱区生态环境知识资源中心(Arid): Nonfinite-modality data augmentation for brain image registration

Arid

DOI	10.1016/j.compbiomed.2022.105780
	Nonfinite-modality data augmentation for brain image registration
	He, Yuanbo; Wang, Aoyu; Li, Shuai; Yang, Yikang; Hao, Aimin
通讯作者	Li, S
来源期刊	COMPUTERS IN BIOLOGY AND MEDICINE
ISSN	0010-4825
EISSN	1879-0534
出版年	2022
卷号	147
英文摘要	Brain image registration is fundamental for brain medical image analysis. However, the lack of paired images with diverse modalities and corresponding ground truth deformations for training hinder its development. We propose a novel nonfinite-modality data augmentation for brain image registration to combat this. Specifically, some available whole-brain segmentation masks, including complete fine brain anatomical structures, are collected from the actual brain dataset, OASIS-3. One whole-brain segmentation mask can generate many nonfinite-modality brain images by randomly merging some fine anatomical structures and subsequently sampling the intensities for each fine anatomical structure using random Gaussian distribution. Furthermore, to get more realistic deformations as the ground truth, an improved 3D Variational Auto-encoder (VAE) is proposed by introducing the intensity-level reconstruction loss and the structure-level reconstruction loss. Based on the generated images and trained improved 3D VAE, a new Synthetic Nonfinite-Modality Brain Image Dataset (SNMBID) is created. Experiments show that pre-training on SNMBID can improve the accuracy of registration. Notably, SNMBID can be a landmark for evaluating other brain registration methods, and the model trained on the SNMBID can be a baseline for the brain image registration task. Our code is available at https://github.com/MangoWAY/SMIBID_BrainRegistration.
英文关键词	Nonfinite-modality Data augmentation Improved 3D VAE Brain image registration
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000833546500004
WOS关键词	ALGORITHMS ; MRI
WOS类目	Biology ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Mathematical & Computational Biology
WOS研究方向	Life Sciences & Biomedicine - Other Topics ; Computer Science ; Engineering ; Mathematical & Computational Biology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/392189
推荐引用方式 GB/T 7714	He, Yuanbo,Wang, Aoyu,Li, Shuai,et al. Nonfinite-modality data augmentation for brain image registration[J],2022,147.
APA	He, Yuanbo,Wang, Aoyu,Li, Shuai,Yang, Yikang,&Hao, Aimin.(2022).Nonfinite-modality data augmentation for brain image registration.COMPUTERS IN BIOLOGY AND MEDICINE,147.
MLA	He, Yuanbo,et al."Nonfinite-modality data augmentation for brain image registration".COMPUTERS IN BIOLOGY AND MEDICINE 147(2022).