Neural implicit surface reconstruction of freehand 3D ultrasound volume with geometric constraints

doi:10.1016/j.media.2024.103305

	Neural implicit surface reconstruction of freehand 3D ultrasound volume with geometric constraints
	Chen, Hongbo1,2,3 ; Kumaralingam, Logiraj 4; Zhang, Shuhang1 ; Song, Sheng1 ; Zhang, Fayi1 ; Zhang, Haibin1 ; Pham, Thanh-Tu 4,5; Punithakumar, Kumaradevan 4; Lou, Edmond H. M.5,6; Zhang, Yuyao1 ; Le, Lawrence H.4,5; Zheng, Rui1,7
	2024-12-01
发表期刊	MEDICAL IMAGE ANALYSIS (IF:10.7[JCR-2023],11.9[5-Year])
ISSN	1361-8415
EISSN	1361-8423
卷号	98
DOI	10.1016/j.media.2024.103305
摘要	Three-dimensional (3D) freehand ultrasound (US) is a widely used imaging modality that allows non-invasive imaging of medical anatomy without radiation exposure. Surface reconstruction of US volume is vital to acquire the accurate anatomical structures needed for modeling, registration, and visualization. However, traditional methods cannot produce a high-quality surface due to image noise. Despite improvements in smoothness, continuity, and resolution from deep learning approaches, research on surface reconstruction in freehand 3D US is still limited. This study introduces FUNSR, a self-supervised neural implicit surface reconstruction method to learn signed distance functions (SDFs) from US volumes. In particular, FUNSR iteratively learns the SDFs by moving the 3D queries sampled around volumetric point clouds to approximate the surface, guided by two novel geometric constraints: sign consistency constraint and on-surface constraint with adversarial learning. Our approach has been thoroughly evaluated across four datasets to demonstrate its adaptability to various anatomical structures, including a hip phantom dataset, two vascular datasets and one publicly available prostate dataset. We also show that smooth and continuous representations greatly enhance the visual appearance of US data. Furthermore, we highlight the potential of our method to improve segmentation performance, and its robustness to noise distribution and motion perturbation.
关键词	Freehand 3D ultrasound Self-supervised surface reconstruction Implicit neural representation Signed distance function Ultrasonic imaging Anatomical structures Freehand three-dimensional ultrasound Geometric constraint Implicit surfaces Neural representations Surfaces reconstruction Ultrasound volume
URL	查看原文
收录类别	SCI ; EI
语种	英语
资助项目	Natural Science Foundation of China (NSFC)["12074258","62071299"] ; Alberta Innovates-Accelerating Innovations into CarE (AICE) program, Canada[RES0056222]
WOS研究方向	Computer Science ; Engineering ; Radiology, Nuclear Medicine & Medical Imaging
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Radiology, Nuclear Medicine & Medical Imaging
WOS记录号	WOS:001299536700001
出版者	ELSEVIER
EI入藏号	20243416911812
EI主题词	Self-supervised learning
EI分类号	1101.2.1 ; 746 Imaging Techniques ; 753.3 Ultrasonic Applications
原始文献类型	Journal article (JA)
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/349887
专题	信息科学与技术学院信息科学与技术学院_PI研究组_郑锐组信息科学与技术学院_硕士生信息科学与技术学院_本科生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_张玉瑶组
通讯作者	Zheng, Rui
作者单位	1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai 201210, Peoples R China 2.Chinese Acad Sci, Shanghai Adv Res Inst, Shanghai 200050, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Univ Alberta, Dept Radiol & Diagnost Imaging, Edmonton, AB T6G 2R7, Canada 5.Univ Alberta, Dept Biomed Engn, Edmonton, AB T6G 2V2, Canada 6.Univ Alberta, Dept Elect & Comp Engn, Edmonton, AB T6G 1H9, Canada 7.ShanghaiTech Univ, Shanghai Engn Res Ctr Intelligent Vis & Imaging, Shanghai 201210, Peoples R China
第一作者单位	信息科学与技术学院
通讯作者单位	信息科学与技术学院; 上海科技大学
第一作者的第一单位	信息科学与技术学院
推荐引用方式 GB/T 7714	Chen, Hongbo,Kumaralingam, Logiraj,Zhang, Shuhang,et al. Neural implicit surface reconstruction of freehand 3D ultrasound volume with geometric constraints[J]. MEDICAL IMAGE ANALYSIS,2024,98.
APA	Chen, Hongbo.,Kumaralingam, Logiraj.,Zhang, Shuhang.,Song, Sheng.,Zhang, Fayi.,...&Zheng, Rui.(2024).Neural implicit surface reconstruction of freehand 3D ultrasound volume with geometric constraints.MEDICAL IMAGE ANALYSIS,98.
MLA	Chen, Hongbo,et al."Neural implicit surface reconstruction of freehand 3D ultrasound volume with geometric constraints".MEDICAL IMAGE ANALYSIS 98(2024).