Freehand 3D Ultrasound Reconstruction Algorithms—A Review

Solberg, Ole Vegard; Lindseth, Frank; Torp, Hans; Blake, Richard E.; Hernes, Toril A. Nagelhus

doi:10.1016/j.ultrasmedbio.2007.02.015

Cited by 190 publications

(136 citation statements)

References 28 publications

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“…Please refer to [13,14] for a review of freehand 3D US volume reconstruction algorithms. The different volume reconstruction algorithms have been classified into three groups in [13]: Voxel-Based Methods (VBM), Pixel-Based Methods (PBM), and Function-Based Methods (FBM). More papers about volume reconstruction methods can be found in references [15][16][17][18].…”

Section: Volume Reconstruction For Freehand 3d Ultrasound Imagingmentioning

confidence: 99%

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

Deng

Jiang

et al. 2016

Applied Sciences

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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.

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Section: Volume Reconstruction For Freehand 3d Ultrasound Imagingmentioning

confidence: 99%

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

Deng

Jiang

et al. 2016

Applied Sciences

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“…Several methods have been proposed in the literature for ultrasound volume reconstruction. 1 While in the past they had been generally satisfactory, in the modern era of real-time 3-D ultrasound image guidance, their manifest shortcomings limit further progress. This paper introduces a new method to significantly improve on existing ultrasound volume reconstruction techniques.…”

Section: Purposementioning

confidence: 99%

“…1 Function-based methods use input image pixels to create three-dimensional mathematical functions, which are then used to estimate voxel intensities. These are heavy on computation which can result in long computation times, 1,2 and blurring may also be noticeable. 2,3 Voxel-based methods estimate voxel intensities as a function of nearby images.…”

Section: Technical Backgroundmentioning

confidence: 99%

Hole filling with oriented sticks in ultrasound volume reconstruction

et al. 2015

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Abstract. Volumes reconstructed from tracked planar ultrasound images often contain regions where no information was recorded. Existing interpolation methods introduce image artifacts and tend to be slow in filling large missing regions. Our goal was to develop a computationally efficient method that fills missing regions while adequately preserving image features. We use directional sticks to interpolate between pairs of known opposing voxels in nearby images. We tested our method on 30 volumetric ultrasound scans acquired from human subjects, and compared its performance to that of other published hole-filling methods. Reconstruction accuracy, fidelity, and time were improved compared with other methods.

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“…Real time 3D ultrasound imaging is used in cardiology, but gives a limited sector, and is not yet adapted to abdominal imaging. A possible alternative would be to obtain 3D volume by reconstruction of 2D ultrasound slices acquired with position tracking (Solberg et al, 2007). …”

Section: Prediction Of Growth and Rupturementioning

confidence: 99%