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Appl. Sci. 2016, 6(4), 114; doi:10.3390/app6040114

Quantitative Assessment of Variational Surface Reconstruction from Sparse Point Clouds in Freehand 3D Ultrasound Imaging during Image-Guided Tumor Ablation

1,* , 1,†
,
2,†
and
3,†
1
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
2
Opto-Mechatronic Equipment Technology Beijing Area Major Laboratory, Beijing Institute of Petrochemical Technology, Beijing 102617, China
3
Department of Interventional Ultrasound, General Hospital of PLA, Beijing 100853, China
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editor: Chien-Hung Liu
Received: 13 December 2015 / Revised: 9 April 2016 / Accepted: 12 April 2016 / Published: 19 April 2016
View Full-Text   |   Download PDF [5671 KB, uploaded 19 April 2016]   |  

Abstract

Surface reconstruction for freehand 3D ultrasound is used to provide 3D visualization of a VOI (volume of interest) during image-guided tumor ablation surgery. This is a challenge because the recorded 2D B-scans are not only sparse but also non-parallel. To solve this issue, we established a framework to reconstruct the surface of freehand 3D ultrasound imaging in 2011. The key technique for surface reconstruction in that framework is based on variational interpolation presented by Greg Turk for shape transformation and is named Variational Surface Reconstruction (VSR). The main goal of this paper is to evaluate the quality of surface reconstructions, especially when the input data are extremely sparse point clouds from freehand 3D ultrasound imaging, using four methods: Ball Pivoting, Power Crust, Poisson, and VSR. Four experiments are conducted, and quantitative metrics, such as the Hausdorff distance, are introduced for quantitative assessment. The experiment results show that the performance of the proposed VSR method is the best of the four methods at reconstructing surface from sparse data. The VSR method can produce a close approximation to the original surface from as few as two contours, whereas the other three methods fail to do so. The experiment results also illustrate that the reproducibility of the VSR method is the best of the four methods. View Full-Text
Keywords: freehand 3D ultrasound; surface reconstruction; variational surface reconstruction; ball pivoting; Power Crust; Poisson reconstruction; Hausdorff distance freehand 3D ultrasound; surface reconstruction; variational surface reconstruction; ball pivoting; Power Crust; Poisson reconstruction; Hausdorff distance
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Deng, S.; Li, Y.; Jiang, L.; Liang, P. Quantitative Assessment of Variational Surface Reconstruction from Sparse Point Clouds in Freehand 3D Ultrasound Imaging during Image-Guided Tumor Ablation. Appl. Sci. 2016, 6, 114.

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