3-D Calibration Algorithm for Freehand Ultrasound Image

Rao, Yao; Lu, Weisheng; Zhang, Xingyuan; Peng, Yao

doi:10.3923/itj.2013.2554.2560

Cited by 2 publications

(2 citation statements)

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“…For Lasso et al .,[21] Świaątek-Najwer et al .,[22] Rao et al . 's[23] designs, and Plus toolkit,[21] the stack of same-sized N-fiducials and mirrored fiducials would cause near linearity of point sets in the center of the design where it should be the most scanned area. The data acquired from that region would be rank deficient for estimating a transformation matrix.…”

Section: Discussionmentioning

confidence: 99%

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A novel design of N-fiducial phantom for automatic ultrasound calibration

Chatrasingh

Suthakorn

2019

J Med Phys

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Background:Freehand ultrasound (US) is a technique used to acquire three-dimensional (3D) US images using a tracked 2D US probe. Calibrating the probe with a proper calibration phantom improves the precision of the technique and allows several applications in computer-assisted surgery. N-fiducial phantom is widely used due to the robustness of precise fabrication and convenience of use. In principle, the design supports single-frame calibration by providing at least three noncollinear points in 3D space at once. Due to this requirement, most designs contain multiple N-fiducials in unpatterned and noncollinear arrangements. The unpatterned multiple N-fiducials appearing as scattered dots in the US image are difficult to extract, and the extracted data are usually contaminated with noise. In practice, the extraction mostly relied on manual interventions, and calibration with N-fiducial phantom has not yet achieved high accuracy with single or few frame calibrations due to noise contamination.Aims:In this article, we propose a novel design of the N-fiducial US calibration phantom to enable automatic feature extraction with comparable accuracy to multiple frame calibration.Materials and Methods:Along with the design, the Random Sample Consensus (RANSAC) algorithm was used for feature extraction with both 2D and 3D models estimation. The RANSAC feature extraction algorithm was equipped with a closed-form calibration method to achieve automatic calibration.Results:The accuracy, precision, and shape reconstruction errors of the calibration acquired from the experiment were significantly matched with the previous literature reports.Conclusions:The results showed that our proposed method has a high efficiency to perform automatic feature extraction compared to conventional extraction performed by humans.

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Section: Discussionmentioning

confidence: 99%

“…[22] and Rao et al . [23] also calibrated a US probe on a phantom with a similar concept to Plus toolkit. The lateral strands of all fiducials were vertically co-aligned such that two parallel and straight dotted lines visible in scan images served as the landmark for detection.…”

Section: Introductionmentioning

confidence: 99%