2004
DOI: 10.1117/12.535984
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Understanding bone responses in B-mode ultrasound images and automatic bone surface extraction using a Bayesian probabilistic framework

Abstract: 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 t… Show more

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Cited by 68 publications
(39 citation statements)
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“…We therefore used the latter as input to our segmentation method. In order to extract the bone surfaces from these images, we used a combination of the bone probability maps introduced by Jain et al [7] and Foroughi et al [4], and the backward scan line tracing presented by Yan et al [15]. In ultrasound images, reflections from bone surfaces are seen as bright ridges perpendicular to the ultrasound beam.…”
Section: Ultrasound Acquisition and Segmentationmentioning
confidence: 99%
See 1 more Smart Citation
“…We therefore used the latter as input to our segmentation method. In order to extract the bone surfaces from these images, we used a combination of the bone probability maps introduced by Jain et al [7] and Foroughi et al [4], and the backward scan line tracing presented by Yan et al [15]. In ultrasound images, reflections from bone surfaces are seen as bright ridges perpendicular to the ultrasound beam.…”
Section: Ultrasound Acquisition and Segmentationmentioning
confidence: 99%
“…Segmentation of the bone surface from ultrasound images of the spine is still a challenging topic due to noise, artifacts and difficulties in imaging surfaces parallel to the ultrasound beam. A few methods have been described in the literature, ranging from simple ray tracing techniques [15] to more advanced methods based on probability measures [7,4,9] or phase symmetry [13]. Following surface extraction, the segmented bone surfaces are registered using the Iterative Closest Point (ICP) algorithm [2] or the unscented Kalman filter [9].…”
Section: Introductionmentioning
confidence: 99%
“…Accurate segmentation has become a prerequisite for accurate registration. Accurate segmentation is difficult because bone surfaces have inconsistent properties (orientation, density, shape, etc), unclear boundaries, and are often accompanied by artifacts and noise, especially in a modality like US [5,6]. Thus a method that can either solve this problem or bypass it holds promise in image guided navigation systems.…”
Section: Introductionmentioning
confidence: 99%
“…Localization of bone surfaces in US images has been studied [5], and an effective method exists for addressing the constraints of this modality and creating a low-noise bone surface probability map. US images are extremely prone to speckle noise, unusual artifacts and intensity inconsistencies which arise from individual machine settings.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, ultrasound (US) based systems have been introduced in the surgical room for the accurate and mini-invasive intra-operative detection of anatomical points 9 . The US probes are equipped with optical markers, with a singular transducer (A-mode) or with an array of transducers (B-mode).…”
Section: Introductionmentioning
confidence: 99%