Comparison of Freehand 3-D Ultrasound Calibration Techniques Using a Stylus

Hsu, Po-Wei; Treece, Graham M.; Prager, Richard W.; Houghton, N; Gee, Andrew H.

doi:10.1016/j.ultrasmedbio.2008.02.015

Cited by 40 publications

(36 citation statements)

References 29 publications

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“…Most importantly, the images of the phantom need to be segmented manually. Although some automatic algorithms may exist (Hsu et al, 2007c), segmentation of isolated points in ultrasonic images are seldom reliable. This is evident from the fact that all of the above mentioned research groups who use a point target segmented their phantom manually.…”

Section: Point Phantom Variantsmentioning

confidence: 99%

“…Gooding et al (2005) placed a cross-wire through the centre of the sphere to ensure good alignment, while maintaining automatic segmentation. Hsu et al (2007c) scanned a phantom consisting of two cones joining at a circle. The centre of this circle serves as the virtual point phantom as shown in Figure 4.…”

Section: Point Phantom Variantsmentioning

confidence: 99%

“…Hence alignment is a major source of error. Hsu et al (2007c) designed a Cambridge stylus with a thick shaft. This shaft is thinned at a point precisely 20mm above the tip of the stylus.…”

Section: Stylusmentioning

confidence: 99%

“…Hsu et al (2007c) pointed out that for a reliable optimisation, the scales needs to be found explicitly and fixed before optimisation. …”

Section: Stylusmentioning

confidence: 99%

“…The figures in this table are therefore directly comparable. Where a citation is missing in the first column, we have performed calibrations with the same ultrasound machine and settings as the ones used by Hsu et al (2007c), so that the results are comparable.…”

Section: Choosing a Phantommentioning

confidence: 99%

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Freehand 3D Ultrasound Calibration: A Review

Hsu

Prager

Gee

et al.

Advanced Imaging in Biology and Medicine

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Freehand three-dimensional ultrasound is a technique for acquiring ultrasonic data of a 3D volume by recording the trajectory of the ultrasound probe using a position sensor. In planning and registration, a freehand ultrasound systems is used to track a two-dimensional probe. Probe calibration is necessary to find the rigid body transformation from the coordinate system of the B-scan to that of the mobile part of the position sensor. Numerous techniques for this have been developed over the past decade. In this review, we give a comprehensive description of existing calibration techniques and classify them according to the mathematical principles on which they are based. We give a thorough analysis of these approaches based on their accuracy, ease of use, reliability, and speed of calibration. To ensure consistency, these comparisons are done by the authors based on experimental results and not on figures quoted in previous papers.

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Section: Point Phantom Variantsmentioning

confidence: 99%

Section: Point Phantom Variantsmentioning

confidence: 99%

“…Hence alignment is a major source of error. Hsu et al (2007c) designed a Cambridge stylus with a thick shaft. This shaft is thinned at a point precisely 20mm above the tip of the stylus.…”

Section: Stylusmentioning

confidence: 99%

“…Hsu et al (2007c) pointed out that for a reliable optimisation, the scales needs to be found explicitly and fixed before optimisation. …”

Section: Stylusmentioning

confidence: 99%

Section: Choosing a Phantommentioning

confidence: 99%

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Freehand 3D Ultrasound Calibration: A Review

Hsu

Prager

Gee

et al.

Advanced Imaging in Biology and Medicine

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Similarity Registration Problems for 2D/3D Ultrasound Calibration

Vasconcelos

Peebles

Ourselin

et al. 2016

Computer Vision – ECCV 2016

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Abstract. We propose a minimal solution for the similarity registration (rigid pose and scale) between two sets of 3D lines, and also between a set of co-planar points and a set of 3D lines. The first problem is solved up to 8 discrete solutions with a minimum of 2 line-line correspondences, while the second is solved up to 4 discrete solutions using 4 point-line correspondences. We use these algorithms to perform the extrinsic calibration between a pose tracking sensor and a 2D/3D ultrasound (US) curvilinear probe using a tracked needle as calibration target. The needle is tracked as a 3D line, and is scanned by the ultrasound as either a 3D line (3D US) or as a 2D point (2D US). Since the scale factor that converts US scan units to metric coordinates is unknown, the calibration is formulated as a similarity registration problem. We present results with both synthetic and real data and show that the minimum solutions outperform the correspondent non-minimal linear formulations.

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