A jointed feature fusion framework for photoacoustic image reconstruction

doi:10.1016/j.pacs.2022.100442

	A jointed feature fusion framework for photoacoustic image reconstruction
	Lan, Hengrong1,2 ; Yang, Changchun1 ; Gao, Fei1,3
	2023-02-01
发表期刊	PHOTOACOUSTICS (IF:7.1[JCR-2023],7.2[5-Year])
ISSN	2213-5979
卷号	29
发表状态	已发表
DOI	10.1016/j.pacs.2022.100442
摘要	The standard reconstruction of Photoacoustic (PA) computed tomography (PACT) image could cause the artifacts due to interferences or ill-posed setup. Recently, deep learning has been used to reconstruct the PA image with ill-posed conditions. In this paper, we propose a jointed feature fusion framework (JEFF-Net) based on deep learning to reconstruct the PA image using limited-view data. The cross-domain features from limited-view position-wise data and the reconstructed image are fused by a backtracked supervision. A quarter position -wise data (32 channels) is fed into model, which outputs another 3-quarters-view data (96 channels). More-over, two novel losses are designed to restrain the artifacts by sufficiently manipulating superposed data. The experimental results have demonstrated the superior performance and quantitative evaluations show that our proposed method outperformed the ground-truth in some metrics by 135% (SSIM for simulation) and 40% (gCNR for in-vivo) improvement.
关键词	Photoacoustic tomography Deep learning Reconstruction Convolutional neural network
URL	查看原文
收录类别	SCI ; EI ; SCOPUS
语种	英语
资助项目	National Natural Science Foundation of China[61805139] ; United Imaging Intelligence[2019x0203-501-02] ; Double First-Class Initiative Fund of ShanghaiTech University[2022x0203-904-04] ; Shanghai Clinical Research and Trial Center[2022A0305-418-02]
WOS研究方向	Acoustics ; Engineering ; Instruments & Instrumentation ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Acoustics ; Engineering, Biomedical ; Instruments & Instrumentation ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:000912094200001
出版者	ELSEVIER GMBH
EI入藏号	20230513472930
EI主题词	Image reconstruction
EI分类号	461.4 Ergonomics and Human Factors Engineering ; 723.2 Data Processing and Image Processing ; 723.5 Computer Applications ; 741.1 Light/Optics ; 751.1 Acoustic Waves
原始文献类型	Journal article (JA)
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/278842
专题	信息科学与技术学院_博士生信息科学与技术学院_PI研究组_高飞组信息科学与技术学院_硕士生
通讯作者	Gao, Fei
作者单位	1.Shanghai Tech Univ, Shanghai Engn Res Ctr Intelligent Vis & Imaging, Sch Informat Sci & Technol, Hybrid Imaging Syst Lab, Shanghai 201210, Peoples R China 2.Tsinghua Univ, Sch Med, Dept Biomed Engn, Beijing 100084, Peoples R China 3.Shanghai Clin Res & Trial Ctr, Shanghai 201210, Peoples R China
第一作者单位	上海科技大学
通讯作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Lan, Hengrong,Yang, Changchun,Gao, Fei. A jointed feature fusion framework for photoacoustic image reconstruction[J]. PHOTOACOUSTICS,2023,29.
APA	Lan, Hengrong,Yang, Changchun,&Gao, Fei.(2023).A jointed feature fusion framework for photoacoustic image reconstruction.PHOTOACOUSTICS,29.
MLA	Lan, Hengrong,et al."A jointed feature fusion framework for photoacoustic image reconstruction".PHOTOACOUSTICS 29(2023).