An efficient point based registration of intra-operative ultrasound images with MR images for computation of brain shift; A phantom study

Farnia, Parastoo; Ahmadian, Alireza; Khoshnevisan, Alireza; Jaberzadeh, AmirHossein; Serej, Nasim Dadashi; Kazerooni, Anahita Fathi

doi:10.1109/iembs.2011.6091991

Cited by 20 publications

(15 citation statements)

References 9 publications

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“…It is comparable to works that also use blood vessel centerlines for registration, such as the work of Reinertsen et al [166,168,167] and Farnia et al [60] using iUS and Ding et al [42] using a LRS. Farnia et al used the same non-rigid registration method as us, the CPD, but with iUS data.…”

Section: Brain Shift Compensationsupporting

confidence: 67%

Guidance and Visualization for Brain Tumor Surgery

Marreiros¹,

Miguel²

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Image guidance and visualization play an important role in modern surgery to help surgeons perform their surgical procedures. Here, the focus is on neurosurgery applications, in particular brain tumor surgery where a craniotomy (opening of the skull) is performed to access directly the brain region to be treated. In this type of surgery, once the skull is opened the brain can change its shape, and this deformation is known as brain shift. Moreover, the boundaries of many types of tumors are difficult to identify by the naked eye from healthy tissue. The main goal of this work was to study and develop image guidance and visualization methods for tumor surgery in order to overcome the problems faced in this type of surgery.Due to brain shift the magnetic resonance dataset acquired before the operation (preoperatively) no longer corresponds to the anatomy of the patient during the operation (intraoperatively). For this reason, in this work methods were studied and developed to compensate for this deformation. To guide the deformation methods, information of the superficial vessel centerlines of the brain was used. A method for accurate (approximately 1 mm) reconstruction of the vessel centerlines using a multiview camera system was developed. It uses geometrical constraints, relaxation labeling, thin plate spline filtering and finally mean shift to find the correct correspondences between the camera images.A complete non-rigid deformation pipeline was initially proposed and evaluated with an animal model. From these experiments it was observed that although the traditional non-rigid registration methods (in our case coherent point drift) were able to produce satisfactory vessel correspondences between preoperative and intraoperative vessels, in some specific areas the results were suboptimal. For this reason a new method was proposed that combined the coherent point drift and thin plate spline semilandmarks. This combination resulted in an accurate (below 1 mm) non-rigid registration method, evaluated with simulated data where artificial deformations were performed.Besides the non-rigid registration methods, a new rigid registration method to obtain the rigid transformation between the magnetic resonance dataset and the neuronavigation coordinate systems was also developed.Once the rigid transformation and the vessel correspondences are known, i the thin plate spline can be used to perform the brain shift deformation. To do so, we have used two approaches: a direct and an indirect. With the direct approach, an image is created that represents the deformed data, and with the indirect approach, a new volume is first constructed and only after that can the deformed image be created. A comparison of these two approaches, implemented for the graphics processing units, in terms of performance and image quality, was performed. The indirect method was superior in terms of performance if the sampling along the ray is high, in comparison to the voxel grid, while the direct was superior otherwise. The image quality an...

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Section: Brain Shift Compensationsupporting

confidence: 67%

Guidance and Visualization for Brain Tumor Surgery

Marreiros¹,

Miguel²

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“…Some of these problems in working with phantom were already observed and resolved in previous studies that were conducted by the authors of the present report [1,21]. In this phantom study, the main difficulties were related to the acquisition of surface data.…”

Section: Discussionmentioning

confidence: 63%

“…We relied on our previous work that used a phantom in which the brain shift was calculated based on the registration of MRI and US images [21]. The idea of using the elasticity concept as a mechanism for precise and repeatable deformation suitable for MR or CT imaging was used as the minimum required specifications for our study.…”

Section: Brain Phantommentioning

confidence: 99%

Estimation of intraoperative brain shift by combination of stereovision and doppler ultrasound: phantom and animal model study

et al. 2015

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The proposed projected surface imaging in conjunction with the Doppler US data combined in a powerful biomechanical model can result an acceptable performance in calculation of deformation during surgical navigation. However, the projected landmark method is sensitive to ambient light and surface conditions and the Doppler ultrasound suffers from noise and 3D image construction problems, the combination of these two methods applied on a FEM has an eligible performance.

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“…As we already showed in our previous work [14], the CPD algorithm requires considerable computational cost therefore it is not suitable for real time registration.…”

Section: Introductionmentioning

confidence: 90%

On the performance of improved ICP algorithms for registration of intra-ultrasound with pre-MR images; a phantom study

Farnia

Ahmadian

Sedighpoor

et al. 2012

2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Ultrasound imaging as a simple and being real time has been found very applicable for intra-operative updates of pre-operative MRI data in image guided neurosurgery system. The main challenge here is the presence of speckle noise which influences the accuracy of registration of US-MR images, intra-operatively. In this paper the performance of two improved versions of the well known Iterative Closest Point (ICP) algorithms to deal with noise and outliers are considered and compared with conventional ICP method. To perform this study in a condition close to real clinical setting, a PVA-C brain phantom is made. As the results show improved versions of ICP are found more robust and precise than ICP algorithms in the presence of noise and outliers. Then the effect of various de-noising methods including diffusion filters on the accuracy of point-based registration is evaluated. The role of a proper diffusion filter for de-noising of US images has also improved the performance of the ICP algorithm and its variants about 35% and 20%, respectively.

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An efficient point based registration of intra-operative ultrasound images with MR images for computation of brain shift; A phantom study

Cited by 20 publications

References 9 publications

Guidance and Visualization for Brain Tumor Surgery

Guidance and Visualization for Brain Tumor Surgery

Estimation of intraoperative brain shift by combination of stereovision and doppler ultrasound: phantom and animal model study

On the performance of improved ICP algorithms for registration of intra-ultrasound with pre-MR images; a phantom study

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