Topology correction of segmented medical images using a fast marching algorithm

We present here a new method for correcting the topology of objects segmented from medical images. Whereas previous techniques alter a surface obtained from a binary segmentation of the object, our technique can be applied directly to the image intensities of a probabilistic or fuzzy segmentation, thereby propagating the topology for all isosurfaces of the object. From an analysis of topological changes and critical points in implicit surfaces, we derive a topology propagation algorithm that enforces any desired topology using a fast marching technique. The method has been applied successfully to the correction of the cortical gray matter/white matter interface in segmented brain images and is publicly released as a software plug-in for the MIPAV package.     

Implicit Fitting Using Radial Basis Functions with Ellipsoid Constraint

Implicit planar curve and surface fitting to a set of scattered points plays an important role in solving a wide variety of problems occurring in computer graphics modelling, computer graphics animation, and computer assisted surgery. The fitted implicit surfaces can be either algebraic or non‐algebraic. The main problem with most algebraic surface fitting algorithms is that the surface fitted to a given data set is often unbounded, multiple sheeted, and disconnected when a high degree polynomial is used, whereas a low degree polynomial is too simple to represent general shapes. Recently, there has been increasing interest in non‐algebraic implicit surface fitting. In these techniques, one popular way of representing an implicit surface has been the use of radial basis functions. This type of implicit surface can represent various shapes to a high level of accuracy. In this paper, we present an implicit surface fitting algorithm using radial basis functions with an ellipsoid constraint. This method does not need to build interior and exterior layers for the given data set or to use information on surface normal but still can fit the data accurately. Furthermore, the fitted shape can still capture the main features of the object when the data sets are extremely sparse. The algorithm involves solving a simple general eigen‐system and a computation of the inverse or psedo‐inverse of a matrix, which is straightforward to implement.     

Automatic Reconstruction of Unstructured 3D Data: Combining a Medial Axis and Implicit Surfaces

This paper presents a new method that combines a medial axis and implicit surfaces in order to reconstruct a 3D solid from an unstructured set of points scattered on the object's surface. The representation produced is based on iso-surfaces generated by skeletons, and is a particularly compact way of defining a smooth free-form solid. The method is based on the minimisation of an energy representing a “distance” between the set of data points and the iso-surface, resembling previous reserach¹⁹. Initialisation, however, is more robust and efficient since there is computation of the medial axis of the set of points. Instead of subdividing existing skeletons in order to refine the object's surface, a new reconstruction algorithm progressively selects skeleton-points from the pre- computed medial axis using an heuristic principle based on a “local energy” criterion. This drastically speeds up the reconstruction process. Moreover, using the medial axis allows reconstruction of objects with complex topology and geometry, like objects that have holes and branches or that are composed of several connected components. This process is fully automatic. The method has been successfully applied to both synthetic and real data.     

基于椭球约束的径向基函数隐式曲面重建

对三维点云进行隐式曲面重建是解决虚拟现实等方面所存在问题的关键。本文提出 了一种基于椭球约束的径向基函数隐式曲面建模的算法,该方法在仅有点云信息的前提下仍能够 非常精确地拟合点云数据。当点云稀疏时拟合后的模型可以非常好地保证模型的主要特征,但对 于拟合大规模数据点集时,模型会出现冗余现象,保特征效果不理想且效率低下。需将点云进行 适当分割,然后并行拟合被分割点云并将它们进行光滑拼接处理。实验效果表明该算法保特征效 果非常好且效率明显提高。     

Robust creation of implicit surfaces from polygonal meshes

Implicit surfaces are used for a number of tasks in computer graphics, including modeling soft or organic objects, morphing, collision detection, and constructive solid geometry. Although operating on implicit surfaces is usually straightforward, creating them is not. We introduce a practical method for creating implicit surfaces from polygonal models that produces high-quality results for complex surfaces. Whereas much previous work in implicit surfaces has been done with primitives such as "blobbies," we use implicit surfaces based on a variational interpolation technique (the three-dimensional generalization of thin-plate interpolation). Given a polygonal mesh, we convert the data to a volumetric representation to use as a guide for creating the implicit surface iteratively. We begin by seeding the surface with a number of constraint points through which the surface must pass. Iteratively, additional constraints are added; the resulting surfaces are evaluated, and the errors guide the placement of subsequent constraints. We have applied our method successfully to a variety of polygonal meshes and consider it to be robust     

Adaptive Sampling of Implicit Surfaces for Interactive Modelling and Animation

This paper presents a new adaptive sampling method for implicit surfaces that can be used in both interactive modelling and animation. The algorithm samples implicit objects composed of blending primitives and efficiently maintains this sampling over time, even when their topology changes (during fractures and fusions). It provides two complementary modes of immediate visualization: displaying “scales” lying on the surface, or a “primitive-wise” polygonization. The sampling method efficiently avoids unwanted blending between different parts of an object. Moreover, it can be used for partitioning an implicit surface into local bounding boxes that will accelerate collision detection during animation and ray-intersections during final rendering.     

Simultaneous Surface Approximation and Segmentation of Complex Objects

Deformable models represent a useful approach to approximate objects from collected data points. We propose to augment the basic approaches designed to handle mostly compact objects or objects of known topology.Our approach can fit simultaneously more than one curve or surface to approximate multiple topologically complex objects by using (1) the residual data points, (2) the badly fitting parts of the approximating surface, and (3) appropriate Boolean operations. In 2-D, B-snakes [3] are used to approximate each object (pattern). In 3-D, an analytical surface representation, based on the elements detected, is presented. The global representation of a 3-D object, in terms of elements and their connection, takes the form of B-spline and Bézier surfaces. A Bézier surface is used to connect different elements, and the connecting surface itself conforms to the data points nearby through energy minimization. This way, aG¹continuity surface is achieved for the underlying 3-D object.We present experiments on synthetic and real data in 2-D and 3-D. In these experiments, multiple complex patterns and objects with through holes are segmented. The system proceeds automatically without human interaction or any prior knowledge of the topology of the underlying object.     

Geometry-aware domain decomposition for T-spline-based manifold modeling

This paper presents a new and effective method to construct manifold T-splines of complicated topology/geometry. The fundamental idea of our novel approach is the geometry-aware object segmentation, by which an arbitrarily complicated surface model can be decomposed into a group of disjoint components that comprise branches, handles, and base patches. Such a domain decomposition simplifies objects of arbitrary topological type into a family of genus-zero/one open surfaces, each of which can be conformally parameterized into a set of rectangles. In contrast to the conventional decomposition approaches, our method can guarantee that the cutting locus are consistent on the parametric domain. As a result, the resultant T-splines of decomposed components are automatically glued and have high-order continuity everywhere except at the extraordinary points. We show that the number of extraordinary points of the domain manifold is bounded by the number of segmented components. Furthermore, the entire mesh-to-spline data conversion pipeline can be implemented with full automation, and thus, has potential in shape modeling and reverse engineering applications of complicated real-world objects.     

The Alignment of Objects with Smooth Surfaces

This paper examines the recognition of rigid objects bounded by smooth surfaces, using an alignment approach. The projected image of such an object changes during rotation in a manner that is generally difficult to predict. An approach to this problem is suggested, using the 3D surface curvature at the points along the silhouette. The curvature information requires a single number for each point along the object′s silhouette, the radial curvature at the point. We have implemented this method and tested it on images of complex 3D objects. Models of the viewed objects were acquired using three images of each object. The implemented scheme was found to give accurate predictions of the objects′ appearances for large transformations. Using this method, a small number of (viewer-centered) models can be used to predict the new appearance of an object from any given viewpoint.     

The Scale Method for Blending Operations in Functionally-Based Constructive Geometry

This paper presents a scale method for developing high dimensional scale functions to blend implicitly defined objects. Scale functions are differentiable on the entire domain except the origin, provide blending range control, and behave like Min/Max operators everywhere, so even a successive composition of blending operations containing overlapped blending regions can be generated smoothly. Because the scale method is a generalized method, implicit or parametric curves, such as cubic Bezier curves, rational conic curves, and implicit conics and hyper‐ellipsoids, can be used to develop scale functions. As a result, it can enhance the flexibility of generating the implicitly blending surfaces in Ricci's constructive geometry, soft objects modeling, and implicit sweep objects. ACM CSS: I.3.5 Computer Graphics—Computational Geometry and Object Modeling ‐ Curve, surface, solid and object representations     

An analytical representation of conformal mapping for genus-zero implicit surfaces and its application to surface shape similarity assessment

This paper develops an analytical representation of conformal mapping for genus-zero implicit surfaces based on algebraic polynomial functions, and its application to surface shape similarity assessment. Generally, the conformal mapping often works as a tool of planar or spherical parameterization for triangle mesh surfaces. It is further exploited for implicit surface matching in this study. The method begins with discretizing one implicit surface by triangle mesh, where a discrete harmonic energy model related to both the mesh and the other implicit surface is established based on a polynomial-function mapping. Then both the zero-center constraint and the landmark constraints are added to the model to ensure the uniqueness of mapping result with the Möbius transformation. By searching optimal polynomial coefficients with the Lagrange–Newton method, the analytical representation of conformal mapping is obtained, which reveals all global and continuous one-to-one correspondent point pairs between two implicit surfaces. Finally, a shape similarity assessment index for (two) implicit surfaces is proposed through calculating the differences of all the shape index values among those corresponding points. The proposed analytical representation method of conformal mapping and the shape assessment index are both verified by the simulation cases for the closed genus-zero implicit surfaces. Experimental results show that the method is effective for genus-zero implicit surfaces, which will offer a new way for object retrieval and manufactured surface inspection.     

Proximity Queries Between Convex Objects: An Interior Point Approach for Implicit Surfaces

This paper presents a general method for exact distance computation between convex objects represented as intersections of implicit surfaces. Exact distance computation algorithms are particularly important for applications involving objects that make intermittent contact, such as in dynamic simulations and in haptic interactions. They can also be used in the narrow phase of hierarchical collision detection. In contrast to geometric approaches developed for polyhedral objects, we formulate the distance computation problem as a convex optimization problem. We use an interior point method to solve the optimization problem and demonstrate that, for general convex objects represented as implicit surfaces, interior point approaches are globally convergent, and fast in practice. Further, they provide polynomial-time guarantees for implicit surface objects when the implicit surfaces have self-concordant barrier functions. We use a primal-dual interior point algorithm that solves the Karush-Kuhn-Tucker (KKT) conditions obtained from the convex programming formulation. For the case of polyhedra and quadrics, we establish a theoretical time complexity of O(n^1.5), where n is the number of constraints. We present implementation results for example implicit surface objects, including polyhedra, quadrics, and generalizations of quadrics such as superquadrics and hyperquadrics, as well as intersections of these surfaces. We demonstrate that in practice, the algorithm takes time linear in the number of constraints, and that distance computation rates of about 1 kHz can be achieved. We also extend the approach to proximity queries between deforming convex objects. Finally, we show that continuous collision detection for linearly translating objects can be performed by solving two related convex optimization problems. For polyhedra and quadrics, we establish that the computational complexity of this problem is also O(n^1.5).     

Creating and Rendering Convolution Surfaces

Implicit surfaces obtained by convolution of multi-dimensional primitives with some potential function, are a generalisation of popular implicit surface models: blobs, metaballs and soft objects. These models differ in their choice of potential function but agree upon the use of underlying modelling primitives, namely, points. In this paper a method is described for modelling and rendering implicit surfaces built upon an expanded set of skeletal primitives: points, line segments, polygons, arcs and planes. An analytical solution to the convolution is described. This solution offers a more accurate and robust representation of the resultant implicit surface than previous methods. An algorithm for ray-tracing the surfaces formed through convolution of any combination of these primitives is also outlined.     

Computing stable poses of piecewise smooth objects

When a three dimensional object is known to be lying on a planar surface, its pose is restricted from six to three degrees of freedom. Computer vision algorithms can exploit the few stable poses of modeled objects to simplify scene interpretation and more accurately determine object location. This paper presents necessary and sufficient conditions for the pose of a piecewise smooth curved three-dimensional object to be stable. For objects whose surfaces are represented by implicit algebraic equations, these conditions can be expressed as systems of polynomial equations that are readily solved by homotopy continuation. Examples from the implemented algorithm are presented.     

隐含多项式曲线曲面拟合次数的确定研究

选用合适次数的隐含多项式曲线曲面描述目标物体是处理和识别目标物体的关键,因而需要在理论上解决隐含多项式曲线或者曲面的次数确定问题.根据目标物体本身的特征,从理论上得出隐含多项式曲线描述物体的次数确定定理,并给出了具体计算公式.该方法首先由给定物体边界的轮廓检测出其驻点数,然后根据驻点数得到拟合隐含多项式曲线方程次数的下界,进而推广到三维物体的隐含多项式曲面拟合次数的确定.最后给出的应用实例进一步验证了算法的有效性与可操作性.     

G 2 interpolation and blending on surfaces

We introduce a method for curvature-continuous (G ²) interpolation of an arbitrary sequence of points on a surface (implicit or parametric) with prescribed tangent and geodesic curvature at every point. The method can also be used forG ² blending of curves on surfaces. The interpolation/blending curve is the intersection curve of the given surface with a functional spline (implicit) surface. For the construction of blending curves, we derive the necessary formulas for the curvature of the surfaces. The intermediate results areG ² interpolation/blending methods in IR².     

An Eulerian approach for constructing a map between surfaces with different topologies

3D objects of the same kind often have different topologies, and finding correspondence between them is important for operations such as morphing, attribute transfer, and shape matching. This paper presents a novel method to find the surface correspondence between topologically different surfaces. The method is characterized by deforming the source polygonal mesh to match the target mesh by using the intermediate implicit surfaces, and by performing a topological surgery at the appropriate locations on the mesh. In particular, we propose a mathematically well‐defined way to detect the topology change of surface by finding the non‐degenerate saddle points of the velocity fields that tracks implicit surfaces. We show the effectiveness and possible applications of the proposed method through several experiments.     

基于BP神经网络的隐式曲线构造方法

隐式曲线与曲面是当前计算机图形学研究的热点之一。通过把BP神经网络与隐式曲线构造原理相结合，提出了一种构造隐式曲线的新方法，即首先由约束点构造神经网络的输入与输出，把描述物体边界曲线的隐式函数转化为显式函数；然后用BP神经网络对此显式函数进行逼近；最后由仿真曲面得到物体边界的拟合曲线。该新方法不同于传统的对显式函数的逼近方法，因为传统方法无法描述封闭的曲线；也不同于基于优化的拟合隐式曲线方法，因为它无须考虑函数的形式或多项式的次数。实验表明，该新方法有很强的物体边界描述能力和缺损修复能力，因而在物体边界重建、缺损图像复原等领域有一定的应用前景。     

An improved star test for implicit polynomial objects

For a given point set, a particular point is called a star if it can see all the boundary points of the set. The star test determines whether a candidate point is a star for a given set. It is a key component of some topology computing algorithms such as Connected components via Interval Analysis (CIA), Homotopy type via Interval Analysis (HIA), etc. Those algorithms decompose the input object using axis-aligned boxes, so that each box is either not intersecting or intersecting with the object and in this later case its center is a star point of the intersection. Graphs or simplicial complexes describing the topology of the objects can be obtained by connecting these star points following different rules. The star test is performed for simple primitive geometric objects, because complex objects can be constructed using Constructive Solid Geometry (CSG), and the star property is preserved via union and intersection. In this paper, we improve the method to perform the test for implicit objects. For a primitive set defined by an implicit polynomial equation, the polynomial is made homogeneous with the introduction of an auxiliary variable, thus the degree of the star condition is reduced. A linear programming optimization is introduced to further improve the performance. Several examples are given to show the experimental results of our method.     

Evolution of T-spline level sets for meshing non-uniformly sampled and incomplete data

Given a large set of unorganized point sample data, we propose a new framework for computing a triangular mesh representing an approximating piecewise smooth surface. The data may be non-uniformly distributed, noisy, and may contain holes. This framework is based on the combination of two types of surface representations, triangular meshes and T-spline level sets, which are implicit surfaces defined by refinable spline functions allowing T-junctions. Our method contains three main steps. Firstly, we construct an implicit representation of a smooth (C ² in our case) surface, by using an evolution process of T-spline level sets, such that the implicit surface captures the topology and outline of the object to be reconstructed. The initial mesh with high quality is obtained through the marching triangulation of the implicit surface. Secondly, we project each data point to the initial mesh, and get a scalar displacement field. Detailed features will be captured by the displaced mesh. Finally, we present an additional evolution process, which combines data-driven velocities and feature-preserving bilateral filters, in order to reproduce sharp features. We also show that various shape constraints, such as distance field constraints, range constraints and volume constraints can be naturally added to our framework, which is helpful to obtain a desired reconstruction result, especially when the given data contains noise and inaccuracies.