Non-rigid registration of breast surfaces using the laplace and diffusion equations

Ong, Rowena E.; Ou, Jao J.; Miga, Michael I.

doi:10.1186/1475-925x-9-8

Cited by 13 publications

(9 citation statements)

References 21 publications

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“…In [63, 65], the solution to Laplace’s equation along the organ surface was generated to extrapolate boundary conditions into the flanking and posterior regions. Components of this approach have been used to assist in non-rigid surface registration of the breast where fiducials were not present [72]. Upon completion of the solution of Laplace’s equation, the boundary conditions assigned to the posterior regions also undergo a norm-sensed application direction change.…”

Section: Methodsmentioning

confidence: 99%

Image‐Guided Abdominal Surgery and Therapy Delivery

Galloway

Herrell

Miga

2012

Journal of Healthcare Engineering

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Image-Guided Surgery has become the standard of care in intracranial neurosurgery providing more exact resections while minimizing damage to healthy tissue. Moving that process to abdominal organs presents additional challenges in the form of image segmentation, image to physical space registration, organ motion and deformation. In this paper, we present methodologies and results for addressing these challenges in two specific organs: the liver and the kidney.

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Section: Methodsmentioning

confidence: 99%

Image‐Guided Abdominal Surgery and Therapy Delivery

Galloway

Herrell

Miga

2012

Journal of Healthcare Engineering

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“…Both methodologies required conditions to be manually specified to various regions of the mesh. While the results presented by Ong et al [11] indicated better performance via the Laplacian method, the diffusion method did not require the difficult task of assigning a boundary condition to the chest wall in both pre-and postdeformed mesh domains. These methods, as well as the TPS method, will be compared to the intensitybased approach in this paper.…”

Section: Introductionmentioning

confidence: 92%

“…As described in [11], the phantom used in this study (hereafter referred to as Phantom 1) was created from an 8% w/v solution of polyvinyl alcohol (Flinn Scientific, Batavia, IL) in an anthropomorphic breast mold. To provide intrinsic fiducial markers, 34 1-mm stainless steel beads were distributed over the phantom directly under its surface.…”

Section: Phantom Experimentsmentioning

confidence: 99%

“…This registration process requires the tedious task of applying and subsequently localizing numerous surface markers within the image space, determining point correspondence, creating a TPS interpolation, and finally calculating a set of Dirichlet boundary conditions for use in the MIE method. Initial attempts to reduce the complexity and level of user interaction have focused on the use of two energy minimization techniques [11]. These techniques relied upon partial differential equation (PDE) solutions of Laplace's equation or the diffusion equation, respectively, across the surface of the organ geometry in the pre-and postdeformed states.…”

Section: Introductionmentioning

confidence: 99%

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Automatic generation of boundary conditions using Demons non-rigid image registration for use in 3D modality-independent elastography

Pheiffer

Miga

2010

Medical Imaging 2010: Visualization, Image-Guided Procedures, and Modeling

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Modality-independent elastography (MIE) is a method of elastography that reconstructs the elastic properties of tissue using images acquired under different loading conditions and a biomechanical model. Boundary conditions are a critical input to the algorithm and are often determined by timeconsuming point correspondence methods requiring manual user input. This study presents a novel method of automatically generating boundary conditions by nonrigidly registering two image sets with a demons diffusion-based registration algorithm. The use of this method was successfully performed in silico using magnetic resonance and X-ray-computed tomography image data with known boundary conditions. These preliminary results produced boundary conditions with an accuracy of up to 80% compared to the known conditions. Demons-based boundary conditions were utilized within a 3-D MIE reconstruction to determine an elasticity contrast ratio between tumor and normal tissue. Two phantom experiments were then conducted to further test the accuracy of the demons boundary conditions and the MIE reconstruction arising from the use of these conditions. Preliminary results show a reasonable characterization of the material properties on this first attempt and a significant improvement in the automation level and viability of the method.

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“…Several researchers have demonstrated that numerical modeling can be used to predict the extent of electroporation in biological tissues [ 57 - 64 ]. Also, numerical modeling and optimization have already been used for optimization of electric pulse parameters for electrochemotherapy of subcutaneous tumors, for tumor ablation with irreversible electroporation [ 63 , 65 - 67 ] and recently, the first deep-seated tumor was treated with electrochemotherapy based on a numerical treatment plan [ 68 ]. However, up to now there exists no such study which would use numerical modeling for optimization of gene electrotransfer.…”

Section: Introductionmentioning

confidence: 99%

Numerical optimization of gene electrotransfer into muscle tissue

et al. 2010

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BackgroundElectroporation-based gene therapy and DNA vaccination are promising medical applications that depend on transfer of pDNA into target tissues with use of electric pulses. Gene electrotransfer efficiency depends on electrode configuration and electric pulse parameters, which determine the electric field distribution. Numerical modeling represents a fast and convenient method for optimization of gene electrotransfer parameters. We used numerical modeling, parameterization and numerical optimization to determine the optimum parameters for gene electrotransfer in muscle tissue.MethodsWe built a 3D geometry of muscle tissue with two or six needle electrodes (two rows of three needle electrodes) inserted. We performed a parametric study and optimization based on a genetic algorithm to analyze the effects of distances between the electrodes, depth of insertion, orientation of electrodes with respect to muscle fibers and applied voltage on the electric field distribution. The quality of solutions were evaluated in terms of volumes of reversibly (desired) and irreversibly (undesired) electroporated muscle tissue and total electric current through the tissue.ResultsLarge volumes of reversibly electroporated muscle with relatively little damage can be achieved by using large distances between electrodes and large electrode insertion depths. Orienting the electrodes perpendicular to muscle fibers is significantly better than the parallel orientation for six needle electrodes, while for two electrodes the effect of orientation is not so pronounced. For each set of geometrical parameters, the window of optimal voltages is quite narrow, with lower voltages resulting in low volumes of reversibly electroporated tissue and higher voltages in high volumes of irreversibly electroporated tissue. Furthermore, we determined which applied voltages are needed to achieve the optimal field distribution for different distances between electrodes.ConclusionThe presented numerical study of gene electrotransfer is the first that demonstrates optimization of parameters for gene electrotransfer on tissue level. Our method of modeling and optimization is generic and can be applied to different electrode configurations, pulsing protocols and different tissues. Such numerical models, together with knowledge of tissue properties can provide useful guidelines for researchers and physicians in selecting optimal parameters for in vivo gene electrotransfer, thus reducing the number of animals used in studies of gene therapy and DNA vaccination.

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Non-rigid registration of breast surfaces using the laplace and diffusion equations

Cited by 13 publications

References 21 publications

Image‐Guided Abdominal Surgery and Therapy Delivery

Image‐Guided Abdominal Surgery and Therapy Delivery

Automatic generation of boundary conditions using Demons non-rigid image registration for use in 3D modality-independent elastography

Numerical optimization of gene electrotransfer into muscle tissue

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