Rapid calibration method for registration and 3D tracking of ultrasound images using spatial localizer

Boctor, Emad M.; Jain, Ameet; Choti, Michael A.; Taylor, Russell H.; Fichtinger, Gabor

doi:10.1117/12.479953

Cited by 30 publications

(14 citation statements)

References 10 publications

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“…In some papers, precision is simply defined as calibration reproducibility and referred to as "precision". Some research groups give the variation of the six calibration parameters (Amin et al, 2001;Boctor et al, 2003. Other research groups give the variation of the three calibration translations and each entry in the rotational transformation matrix (Pagoulatos et al, 2001;Leotta, 2004), this is not appropriate since these values are not independent.…”

Section: Precisionmentioning

confidence: 99%

“…Before the stylus was developed enabling the evaluation of point reconstruction accuracy, many groups assessed accuracy by measuring the distances between objects (Leotta et al, 1997;Prager et al, 1998;Blackall et al, 2000;Boctor et al, 2003;Lindseth et al, 2003b;Leotta, 2004;Dandekar et al, 2005;Hsu et al, 2006;Krupa, 2006). This technique is popular because the experiment is easy to set up.…”

Section: Distance Accuracymentioning

confidence: 99%

“…In some rare cases, the scales may be supplied by the manufacturer (Boctor et al, 2003) or by accessing the raw ultrasound signals (Hsu et al, 2006), but this requires special arrangements with the supplier. Otherwise, the scales can be obtained explicitly by using the distance measurement tool provided by the ultrasound machines (Hsu et al, 2006).…”

Section: Point Phantom With a Stylusmentioning

confidence: 99%

“…The user is still required to follow the same complex protocol and scan the phantom from a wide variety of positions and angles. Boctor et al (2003) designed a phantom with a set of parallel wires forming two orthogonal planes. When the set of wires is being scanned, it appears as distinct dots in the shape of a cross.…”

Section: Plane 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: Precisionmentioning

confidence: 99%

Section: Distance Accuracymentioning

confidence: 99%

Section: Point Phantom With a Stylusmentioning

confidence: 99%

Section: Plane 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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“…A significant time consuming part of the procedure is the construction of the bone surface mesh-model from the preoperative CT. To overcome this problem, a direct 3D-3D registration method can be employed [4,15]. Coupling tracked US images [3], a 3D volume of the bone surface can be created. This volume can be directly registered to the preoperative CT, eliminating the need for the time-consuming semi-automatic segmentation process.…”

Section: Introductionmentioning

confidence: 99%

Understanding bone responses in B-mode ultrasound images and automatic bone surface extraction using a Bayesian probabilistic framework

Jain

Taylor

2004

SPIE Proceedings

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The registration of preoperative CT to intra-operative reality systems is a crucial step in Computer Assisted Orthopedic Surgery (CAOS). The intra-operative sensors include 3D digitizers, fiducials, X-rays and Ultrasound (US). Although US has many advantages over others, tracked US for Orthopedic Surgery has been researched by only a few authors. An important factor limiting the accuracy of tracked US to CT registration (1-3mm) has been the difficulty in determining the exact location of the bone surfaces in the US images (the response could range from 2-4mm). Thus it is crucial to localize the bone surface accurately from these images. Moreover conventional US imaging systems are known to have certain inherent inaccuracies, mainly due to the fact that the imaging model is assumed planar. This creates the need to develop a bone segmentation framework that can couple information from various post-processed spatially separated US images (of the bone) to enhance the localization of the bone surface.In this paper we discuss the various reasons that cause inherent uncertainties in the bone surface localization (in Bmode US images) and suggest methods to account for these. We also develop a method for automatic bone surface detection. To do so, we account objectively for the high-level understanding of the various bone surface features visible in typical US images. A combination of these features would finally decide the surface position. We use a Bayesian probabilistic framework, which strikes a fair balance between high level understanding from features in an image and the low level number crunching of standard image processing techniques. It also provides us with a mathematical approach that facilitates combining multiple images to augment the bone surface estimate.

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