RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction
2024-08-14
会议录名称ARXIV (IF:0.402[JCR-2005],0.000[5-Year])
ISSN0302-9743
卷号15004
发表状态已发表
DOIarXiv:2408.07325
摘要

The reconstruction of high-quality shape geometry is crucial for developing freehand 3D ultrasound imaging. However, the shape reconstruction of multi-view ultrasound data remains challenging due to the elevation distortion caused by thick transducer probes. In this paper, we present a novel learning-based framework RoCoSDF, which can effectively generate an implicit surface through continuous shape representations derived from row-column scanned datasets. In RoCoSDF, we encode the datasets from different views into the corresponding neural signed distance function (SDF) and then operate all SDFs in a normalized 3D space to restore the actual surface contour. Without requiring pre-training on large-scale ground truth shapes, our approach can synthesize a smooth and continuous signed distance field from multi-view SDFs to implicitly represent the actual geometry. Furthermore, two regularizers are introduced to facilitate shape refinement by constraining the SDF near the surface. The experiments on twelve shapes data acquired by two ultrasound transducer probes validate that RoCoSDF can effectively reconstruct accurate geometric shapes from multi-view ultrasound data, which outperforms current reconstruction methods. 

关键词Multi-view reconstruction Neural shape representation Freehand 3D ultrasound
会议名称27th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
出版地GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
会议地点Palmeraie Conf Ctr,Marrakesh,MOROCCO
会议日期OCT 06-10, 2024
URL查看原文
收录类别CPCI-S
语种英语
资助项目Natural Science Foundation of China[12074258]
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Software Engineering ; Engineering, Electrical& Electronic
WOS记录号PPRN:91378628
出版者SPRINGER INTERNATIONAL PUBLISHING AG
EISSN1611-3349
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/414213
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_博士生
信息科学与技术学院_PI研究组_马月昕
通讯作者Zheng, Rui
作者单位
1.ShanghaiTech Univ, Sch Informat Sci & Technol, Shanghai, Peoples R China
2.ShanghaiTech Univ, Shanghai Engn Res Ctr Intelligent Vis & Imaging, Shanghai, 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,Gao, Yuchong,Zhang, Shuhang,et al. RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2024.
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