Ultrasound/MRI Overlay with Image Warping for Neurosurgery

Gobbi, David G.; Comeau, Roch M.; Peters, Terry M.

doi:10.1007/978-3-540-40899-4_11

Cited by 52 publications

(39 citation statements)

References 18 publications

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“…The mapping procedure was demonstrated to have an accuracy better than 2 mm. Gobbi et al (2000) demonstrated a similar technique where manually placed landmarks and a thin-plate spline interpolation were used to deform the MR volume to match the ultrasound volume.…”

Section: Manual Registration Of Intraoperative Ultrasoundmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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The displacement and deformation of brain tissue is a major source of error in image-guided neurosurgery systems. We have designed and implemented a method to detect and correct brain shift using pre-operative MR images and intraoperative Doppler ultrasound data and present its validation with both real and simulated data. The algorithm uses segmented vessels from both modalities, and estimates the deformation using a modified version of the iterative closest point (ICP) algorithm. We use the least trimmed squares (LTS) to reduce the number of outliers in the point matching procedure. These points are used to drive a thin-plate spline transform to achieve non-linear registration. Validation was completed in two parts. First, the technique was tested and validated using realistic simulations where the results were compared to the known deformation. The registration technique recovered 75% of the deformation in the region of interest accounting for deformations as large as 20 mm. Second, we performed a PVA-cryogel phantom study where both MR and ultrasound images of the phantom were obtained for three different deformations. The registration results based on MR data were used as a gold standard to evaluate the performance of the ultrasound based registration. On average, deformations of 7.5 mm magnitude were corrected to within 1.6 mm for the ultrasound based registration and 1.07 mm for the MR based registration.

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Section: Manual Registration Of Intraoperative Ultrasoundmentioning

confidence: 99%

Validation of vessel-based registration for correction of brain shift

Reinertsen

Descoteaux

Siddiqi

et al. 2007

Medical Image Analysis

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“…The first strategy is to use intra-operative imaging during surgery to capture and account for brain shift. Modalities such as intra-operative CT, intra-operative MR and intra-operative US have been, or are being, investigated as image-based compensation strategies [2,3,4]. However, unique challenges in each of these modalities have limited their widespread adoption as the de facto brain shift compensation strategy.…”

Section: Introductionmentioning

confidence: 99%

Cortical Shift Tracking Using a Laser Range Scanner and Deformable Registration Methods

Sinha

Duay

Dawant

et al. 2003

Lecture Notes in Computer Science

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A novel brain shift tracking protocol is introduced in this paper which utilizes laser range scan (LRS) data and 2D deformable image registration. This protocol builds on previous efforts to incorporate intra-operative LRS data into a model-updated image guided surgery paradigm for brain shift compensation. The shift tracking method employs the use of a LRS system capable of capturing textures of the intra-operative scene during range data acquisition. Textures from serial range images are then registered using a 2D deformable registration approach that uses local support radial basis functions and mutual information. Given the deformation field provided by the registration, 3D points in serial LRS datasets can then be tracked. Results from this paper indicate that the error associated with tracking brain movement is 1.1mm on average given brain shifts of approximately 20.5mm. Equally important, a strategy is presented to rapidly acquire intraoperative measurements of shift which are compatible with model-based strategies for brain deformation compensation.

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“…In [6], the outlines of the 2D US image are registered to the MR surface using a Chamfer matching technique. In [10,5,4], the 2D US probe is optically tracked and the corresponding MR slice is displayed to the user who marks corresponding points on MR and US slices. Then, a thin plate spline warp is computed to determine the brain shift.…”

Section: Mr/us Registrationmentioning

confidence: 99%