Three-dimensional Deformation Model Research Articles

Geometrically Induced Force Interaction for Three-Dimensional Deformable Models

In this paper, we propose a novel 3-D deformable model that is based upon a geometrically induced external force field which can be conveniently generalized to arbitrary dimensions. This external force field is based upon hypothesized interactions between the relative geometries of the deformable model and the object boundary characterized by image gradient. The evolution of the deformable model is solved using the level set method so that topological changes are handled automatically. The relative geometrical configurations between the deformable model and the object boundaries contribute to a dynamic vector force field that changes accordingly as the deformable model evolves. The geometrically induced dynamic interaction force has been shown to greatly improve the deformable model performance in acquiring complex geometries and highly concave boundaries, and it gives the deformable model a high invariancy in initialization configurations. The voxel interactions across the whole image domain provide a global view of the object boundary representation, giving the external force a long attraction range. The bidirectionality of the external force field allows the new deformable model to deal with arbitrary cross-boundary initializations, and facilitates the handling of weak edges and broken boundaries. In addition, we show that by enhancing the geometrical interaction field with a nonlocal edge-preserving algorithm, the new deformable model can effectively overcome image noise. We provide a comparative study on the segmentation of various geometries with different topologies from both synthetic and real images, and show that the proposed method achieves significant improvements against existing image gradient techniques.

From high-resolution CT data to finite element models: development of an integrated modular framework

New ideas for the extraction of finite element (FE) models from high-resolution computed tomography datasets are presented. The multi-step approach starts with a 3D region-growing algorithm in order to extract the outer voxel based iso-surface. This information is used to compute a voxel model of the cortical shell. The next step provides triangulated surfaces of the outer bone contour. Three-dimensional deformable models using a gradient vector flow and a multi-level mesh resampling are used. These meshes are self-regularising and of high quality. A further step contains a new self correcting cortical shell thickness evaluation algorithm, which results in topological conform smooth inner and outer compact bone iso-surface meshes. Such iso-surfaces can be used for numerically efficient FE models, which are of bio-mechanical and clinical importance. Details of the approach are described and applications with respect to a human proximal femur and vertebral body are shown.

Brain MRI Segmentation with Multiphase Minimal Partitioning: A Comparative Study

This paper presents the implementation and quantitative evaluation of a multiphase three-dimensional deformable model in a level set framework for automated segmentation of brain MRIs. The segmentation algorithm performs an optimal partitioning of three-dimensional data based on homogeneity measures that naturally evolves to the extraction of different tissue types in the brain. Random seed initialization was used to minimize the sensitivity of the method to initial conditions while avoiding the need for a priori information. This random initialization ensures robustness of the method with respect to the initialization and the minimization set up. Postprocessing corrections with morphological operators were applied to refine the details of the global segmentation method. A clinical study was performed on a database of 10 adult brain MRI volumes to compare the level set segmentation to three other methods: “idealized” intensity thresholding, fuzzy connectedness, and an expectation maximization classification using hidden Markov random fields. Quantitative evaluation of segmentation accuracy was performed with comparison to manual segmentation computing true positive and false positive volume fractions. A statistical comparison of the segmentation methods was performed through a Wilcoxon analysis of these error rates and results showed very high quality and stability of the multiphase three-dimensional level set method.

Segmentation of focal cortical dysplasia lesions on MRI using level set evolution

Focal cortical dysplasia (FCD) is the most frequent malformation of cortical development in patients with medically intractable epilepsy. On MRI, FCD lesions are not easily differentiable from the normal cortex and defining their spatial extent is challenging. In this paper, we introduce a method to segment FCD lesions on T1-weighted MRI. It relies on two successive three-dimensional deformable models, whose evolutions are based on the level set framework. The first deformable model is driven by probability maps obtained from three MRI features: cortical thickness, relative intensity and gradient. These features correspond to the visual characteristics of FCD and allow discriminating lesions and normal tissues. In a second stage, the previous result is expanded towards the underlying and overlying cortical boundaries, throughout the whole cortical section. The method was quantitatively evaluated by comparison with manually traced labels in 18 patients with FCD. The automated segmentations achieved a strong agreement with the manuals labels, demonstrating the applicability of the method to assist the delineation of FCD lesions on MRI. This new approach may become a useful tool for the presurgical evaluation of patients with intractable epilepsy related to cortical dysplasia.

A coupled momentum method for modeling blood flow in three-dimensional deformable arteries

Blood velocity and pressure fields in large arteries are greatly influenced by the deformability of the vessel. Moreover, wave propagation phenomena in the cardiovascular system can only be described considering wall deformability since blood is usually described as an incompressible fluid. However, computational methods for simulating blood flow in three-dimensional models of arteries have either considered a rigid wall assumption for the vessel or significantly simplified or reduced geometries. Computing blood flow in deformable domains using standard techniques like the ALE method remains a formidable problem for large, realistic anatomic and physiologic models of the cardiovascular system. We have developed a new method to simulate blood flow in three-dimensional deformable models of arteries. The method couples the equations of the deformation of the vessel wall at the variational level as a boundary condition for the fluid domain. We consider a strong coupling of the degrees-of-freedom of the fluid and the solid domains, and a linear membrane model (enhanced with transverse shear) for the vessel wall. The effect of the vessel wall boundary is therefore added in a monolithic way to the fluid equations, resulting in a remarkably robust scheme. We present here the mathematical formulation of the method and discuss issues related to the fluid–solid coupling, membrane formulation, time integration method, and boundary and initial conditions. Implementation is discussed and results with simple geometries as well as large subject-specific models are presented.

Construction Method of Three-Dimensional Deformable Template Models for Tree-Shaped Organs

In this paper, we propose a construction method of three-dimensional deformable models that represent tree-shaped human organs, such as bronchial tubes, based on results obtained by statistically analyzing the distributions of bifurcation points in the tree-shaped organs. The models are made to be used as standard templates of tree-shaped organs in medical image recognition, and are formed by control points that can be uniquely identified as structural elements of organs such as bifurcation tracheae in bronchial tubes. They can be transfigured based on the statistical validity of relationships between the control points. The optimal state of that transfiguration is determined within the framework of energy minimization. Experimental results from bronchial tubes are shown on actual CT images.

Simulation of blood flow and vessel deformation in three-dimensional, patient-specific models of the cardiovascular system using a novel method for fluid-solid interactions

Blood velocity and pressure fields in large arteries are greatly influenced by the deformability of the vessel. However, computational methods for simulating blood flow in three-dimensional models of arteries have either considered a rigid wall assumption for the vessel or significantly simplified or reduced geometries. Computing blood flow in deformable domains using standard techniques like the ALE method remains a formidable problem for large, realistic anatomic and physiologic models of the cardiovascular system. We have developed a new method to simulate blood flow in three-dimensional deformable models of arteries. The method couples the equations of the deformation of the vessel wall at the variational level as a boundary condition for the fluid domain. We consider a strong coupling of the degrees-of-freedom of the fluid and the solid domains. The effect of the vessel wall boundary is therefore added in a monolithic way to the fluid equations, resulting in a remarkably robust scheme.

Development of extraction method of kidneys from abdominal CT images using a three‐dimensional deformable model

AbstractThis paper presents a method of extraction of kidneys from abdominal CT images using a three‐dimensional deformable model. In the proposed method, an initial surface model is located in an appropriate position of the image and deformed to fit the target's boundaries. Shape feature is incorporated into the deformable model through energy function as a priori knowledge of the target. Concretely, principal curvatures of the model surface are adopted to characterize the geometrical features of the target and its mean and covariance with the neighboring shape are considered when the deformation is demonstrated. We have applied the proposed method to extract kidneys from three‐dimensional abdominal CT images. The experimental results are presented and the effectiveness of the method is discussed in this paper. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(5): 25–36, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10268

A three-dimensional deformable model for segmentation of human prostate from ultrasound images.

Segmentation of human prostate from ultrasound (US) images is a crucial step in radiation therapy, especially in real-time planning for US image-guided prostate seed implant. This step is critical to determine the radioactive seed placement and to ensure the adequate dose coverage of prostate. However, due to the low contrast of prostate and very low signal-to-noise ratio in US images, this task remains as an obstacle. The manual segmentation of this object is time consuming and highly subjective. In this work, we have proposed a three-dimensional (3D) deformable surface model for automatic segmentation of prostate. The model has a discrete structure made from a set of vertices in the 3D space that form triangle facets. The model converges from an initial shape to its equilibrium iteratively, by a weighted sum of the internal and external forces. Internal forces are based on the local curvature of the surface and external forces are extracted from the volumetric image data by applying an appropriate edge filter. We have also developed a method for initialization of the model from a few initial contours that are drawn on different slices. During the deformation, a resampling procedure is used to maintain the resolution of the model. The entire model is applied in a multiscale scheme, which increases the robustness and speed, and guarantees a better convergence. The model is tested on real clinical data and initial results are very promising.

顎関節ＭＲ画像における骨表面の抽出 可変形状モデルの応用

This paper presents a two-step method, based on magnetic resonance (MR) images, for threedimensional reconstruction of osseous components of a temporomandibular joint (TMJ), the mandibular condyle and the fossa. In the first step, images were segmented in order to extract the bony outline (contour) by using a two-dimensional deformable model. An object in the model was extracted by deforming the initial contour located near the object of the image. In the second step, using the surface reconstructed from the extracted contour as the initial surface, a three-dimensional deformable model was applied in order to extract the surface of the object. These procedures were handled semi-automatically. Multi-section 1-mm-thick sagittal images of the right normal TMJ were obtained with a 1.5-T MR system and surface coils by using a FLASH-3 D sequence (TR=50ms, TE=11ms) from an asymptomatic volunteer (male, age 31 years). From these images, the bony surfaces of TMJ were extracted using the above-mentioned method. Even though the extracted surfaces were a little smaller than the surface traced by e xperienced dentists, they showed the normal, anatomical form of TMJ.