@inproceedings{ea30472258d34dd9beee6233a793d4c8,
title = "Feasibility Verification of Radiation-Free Renal Volumetry: A Magnetic Navigation Ultrasound Simulation Framework with Enhanced Point Cloud Completion",
abstract = "This study validates the technical feasibility of three-dimensional kidney reconstruction and volumetric quantification using a single ultrasound modality through magnetic navigation simulation and hierarchical point cloud completion. By synthesizing sparse ultrasound-like sampling data (5 points/cm ) derived from the KiTS21 CT dataset, our enhanced Morphing and Sampling Network (MSN) achieves a 3.618\% volumetric error relative to CT ground truth via tetrahedral reconstruction, while reducing processing time to 30 seconds per case (98.4\% faster than conventional rotating probe systems). The framework demonstrates robust performance in resolving complex anatomical structures under simulated sparse sampling conditions, providing theoretical foundations for radiation-free renal volumetry. This proof-of-concept work establishes core computational principles for ultrasound-based 3D kidney modeling, prioritizing accuracy and efficiency in radiationsensitive clinical applications.",
keywords = "Magnetic Navigation, Point Cloud, Renal Volumetry",
author = "Sikai Ge and Gulong Sun and Wuwei Ma and Junwei Wu and Zexuan Fan and Fei Ma",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 8th International Conference on Big Data and Artificial Intelligence, BDAI 2025 ; Conference date: 22-08-2025 Through 24-08-2025",
year = "2025",
doi = "10.1109/BDAI66031.2025.11325723",
language = "English",
series = "2025 8th International Conference on Big Data and Artificial Intelligence, BDAI 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "372--375",
booktitle = "2025 8th International Conference on Big Data and Artificial Intelligence, BDAI 2025",
}