A realistic phantom for brain-shift simulations

Reinertsen, Ingerid; Collins, D. Louis

doi:10.1118/1.2219091

Cited by 33 publications

(22 citation statements)

References 8 publications

(7 reference statements)

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“…By inflating or deflating the catheter balloon, the phantom would deform in an elastic non-linear manner. A detailed description of the phantom as well as a thorough study of the reproducibility of the deformations can be found in Reinertsen and Collins (2006). The phantom made it possible to test the registration algorithm and segmentation technique as well as the ultrasound imaging setup and the navigation software in a setting with known geometry and simpler deformations than in the human brain.…”

Section: Phantom Study 321 Phantom Preparationmentioning

confidence: 99%

“…To overcome this problem, parts of the smallest tubes were segmented manually. In the future, a possible solution to this problem would be to fill the tubes with a contrast agent prior to MR imaging Reinertsen and Collins, 2006. Following segmentation, centerlines were extracted using the algorithm described in Section 2.3.…”

Section: Mr Imaging and Vessel Segmentationmentioning

confidence: 99%

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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: Phantom Study 321 Phantom Preparationmentioning

confidence: 99%

Section: Mr Imaging and Vessel Segmentationmentioning

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 creation of a physical model capable of depicting the form of the cerebrum in a realistic manner is not trivial due in part to these deep structures. Previous works in creating brain phantoms have either reduced the depth of the sulci [2], or only recreated the brain's form superficially with dessert gelatin molds [3,4]. Although these phantoms bear a gross cursory resemblance to the human cerebrum, they do not accurately depict its anatomy.…”

Section: Introductionmentioning

confidence: 99%

“…This may be due to the structures being smaller than the image resolution or having insufficient contrast of the markers with respect to the surrounding tissues. For instance, Reinertsen and Collins [4] rely on the presence of bubbles in their phantom to act as landmarks for validation. Our goal is to create a triple modality human brain phantom containing anatomically realistic structures and physically realistic texture.…”

Section: Introductionmentioning

confidence: 99%

“…It is a good material for such studies since it has similar texture, mechanical properties such as compressibility and elasticity, and similar water content to many soft tissues [2,4,9,10,11,12,13]. PVA-C has been used in the construction of phantoms for studying a wide variety of tissues including that of the heart [14], breast [10,11], prostate [13], arterial vasculature [8,2], the brain [4,2], as well as their abnormal tissues in the form of lesions and tumours [10,11,13].…”

Section: Introductionmentioning

confidence: 99%

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An Anthropomorphic Polyvinyl Alcohol Triple-Modality Brain Phantom Based on Colin27

Chen

Hellier

Gauvrit

et al. 2010

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2010

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Abstract. We propose a method for the creation of an anatomically and mechanically realistic brain phantom from polyvinyl alcohol cryogel (PVA-C) for validation of image processing methods for segmentation, reconstruction, registration, and denoising. PVA-C is material widely used in medical imaging phantoms for its mechanical similarities to soft tissues. The phantom was cast in a mold designed using the left hemiphere of the Colin27 brain dataset [1] and contains deep sulci, a complete insular region, and an anatomically accurate left ventricle. Marker spheres and inflatable catheters were also implanted to enable good registration and simulate tissue deformation, respectively. The phantom was designed for triple modality imaging, giving good contrast images in computed tomography, ultrasound, and magnetic resonance imaging. Multimodal data acquired from this phantom are made freely available to the image processing community (http://pvabrain.inria.fr) and will aid in the validation and further development of medical image processing techniques.

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An efficient method for estimating soft tissue deformation based on intraoperative stereo image features and point‐based registration

Ahmadian

Serej

Karimifard

et al. 2013

Int J Imaging Syst Tech

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Estimation of soft tissue deformation occurring during image-guided surgery using an easily implemented and accurate method is necessary. Using a stereo camera, this study focuses on two efficient methods for estimating soft tissue deformation. Two methods were proposed to overcome limitations associated with the typical methods used for estimating soft tissue deformation, such as dependence on accuracy of the operator and indentation of skin. The first method is based on Triclops SDK, and the second method is based on projecting a pattern to acquire P-Lands (Projected Landmarks). Based on the proposed methods, surface information is acquired in the form of point clouds of surface point coordinates to the submillimeter accuracy. The reconstructed predeformation threedimensional (3D) point cloud obtained for each method is registered with a modified iterative closest point algorithm to a postdeformation 3D point cloud obtained from the same region of interest. Results were compared with an MRI-MRI registration method as a control. Results are provided as RMS differences between the initial and final coordinates of corresponding points. The average RMS difference for the typical method is 3.53 mm, that for the Triclops SDK method is 2.32 mm, and that for the P-Lands projection method is 2.06 mm. The MRI-MRI registration had an average RMS difference of 1.12 mm. Using MRI-MRI registration as the gold standard, the average error obtained for the typical method was 2.41 mm, that for the first method was 1.2 mm, and that for the second method was 0.94 mm.

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A realistic phantom for brain-shift simulations

Cited by 33 publications

References 8 publications

Validation of vessel-based registration for correction of brain shift

Validation of vessel-based registration for correction of brain shift

An Anthropomorphic Polyvinyl Alcohol Triple-Modality Brain Phantom Based on Colin27

An efficient method for estimating soft tissue deformation based on intraoperative stereo image features and point‐based registration

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