Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease

doi:10.1109/JBHI.2021.3097721

	Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease
	Xingyu Gao 1; Feng Shi 2; Dinggang Shen2,3,4 ; Manhua Liu 5
	2022
发表期刊	IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS (IF:6.7[JCR-2023],7.1[5-Year])
ISSN	2168-2208
卷号	26 期号:1
发表状态	已发表
DOI	10.1109/JBHI.2021.3097721
摘要	With the advance of medical imaging technologies, multimodal images such as magnetic resonance images (MRI) and positron emission tomography (PET) can capture subtle structural and functional changes of brain, facilitating the diagnosis of brain diseases such as Alzheimer's disease (AD). In practice, multimodal images may be incomplete since PET is often missing due to high financial costs or availability. Most of the existing methods simply excluded subjects with missing data, which unfortunately reduced the sample size. In addition, how to extract and combine multimodal features is still challenging. To address these problems, we propose a deep learning framework to integrate a task-induced pyramid and attention generative adversarial network (TPA-GAN) with a pathwise transfer dense convolution network (PT-DCN) for imputation and classification of multimodal brain images. First, we propose a TPA-GAN to integrate pyramid convolution and attention module as well as disease classification task into GAN for generating the missing PET data with their MRI. Then, with the imputed multimodal images, we build a dense convolution network with pathwise transfer blocks to gradually learn and combine multimodal features for final disease classification. Experiments are performed on ADNI-1/2 datasets to evaluate our method, achieving superior performance in image imputation and brain disease diagnosis compared to state-of-the-art methods.
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收录类别	SCI ; SCIE ; EI
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/135736
专题	生物医学工程学院生物医学工程学院_PI研究组_沈定刚组
作者单位	1.Department of Instrument Science and Engineering, School of EIEE, Shanghai Jiao Tong University, Shanghai, China 2.Department of Research and Development, Shanghai United Imaging Intelligence Company, Ltd., Shanghai, China 3.School of Biomedical Engineering, ShanghaiTech University, Shanghai, China 4.Department of Artificial Intelligence, Korea University, Seoul, Republic of Korea 5.MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai, China
推荐引用方式 GB/T 7714	Xingyu Gao,Feng Shi,Dinggang Shen,et al. Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease[J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,2022,26(1).
APA	Xingyu Gao,Feng Shi,Dinggang Shen,&Manhua Liu.(2022).Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease.IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,26(1).
MLA	Xingyu Gao,et al."Task-Induced Pyramid and Attention GAN for Multimodal Brain Image Imputation and Classification in Alzheimer's Disease".IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 26.1(2022).